ITS2 bioinformatics
Kelsey Schoenemann
2024-11-13
Set-Up workspace
There are two possible directories containing sequence data: * /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/rbcL ** this directory is for running the code on UVA’s HPC Rivanna
- /Users/kelseyschoenemann/Desktop/Bioinformatics/2024-09-27_MiSeq_v3/ITS2 ** this directory is for running the code on my local machine
(you can easily switch between these two directories by selecting the old path, up to & including Bioinformatics, and hit Cmd F to bring up Find & Replace tool, then copy-paste the new path into the Replace box and hit All. There should be 25 replacements if you skip the very first instance above)
Summary of Files / Directories
/scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2 *Ns & primers present (raw files)
/scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/filtN *Ns removed, primers present (pre-filtered)
/scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt *Ns & primers removed (cutadapted)
/scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered *Ns & primers removed and filter & trimmed (filtered)
- List of primers used * We used plant universal primers: iTru_ITS2_S2F (ATGCGATACTTGGTGTGAAT) & iTru_ITS2_4R (TCCTCCGCTTATTGATATGC) iTru_rbcL2 (TGGCAGCATTYCGAGTAACTC) & iTru_rbcLa-R (GTAAAATCAAGTCCACCRCG)
Load packages
#install packages with BiocManager (if you have anaconda)
# if (!requireNamespace("BiocManager", quietly = TRUE))
# install.packages("BiocManager")
# BiocManager::install("dada2", version = "3.16")
# BiocManager::install(c("DECIPHER", "ShortRead", "phyloseq")"))
# BiocManager::install("decontam")
library(devtools); packageVersion("devtools")## Loading required package: usethis## [1] '2.4.5'library(dada2); packageVersion("dada2")## Loading required package: Rcpp## [1] '1.32.0'library(ShortRead); packageVersion("ShortRead")## Loading required package: BiocGenerics##
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## distance## [1] '1.48.0'library(ggplot2); packageVersion("ggplot2")## [1] '3.5.1'#library(decontam); packageVersion("decontam")
#devtools::install_github("benjjneb/dada2", ref="v1.16") # change the ref argument to get other versionsSet working directory
setwd("/scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2")
path <- "/scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2" ## CHANGE ME to the directory containing the fastq files.
head(list.files(path, pattern = "*.fastq"))## [1] "ITS2-2020-6-16-H1_S31_L001_R1_001.fastq"
## [2] "ITS2-2020-6-16-H1_S31_L001_R2_001.fastq"
## [3] "ITS2-2020-6-16-H5_S32_L001_R1_001.fastq"
## [4] "ITS2-2020-6-16-H5_S32_L001_R2_001.fastq"
## [5] "ITS2-2020-6-16-H6_S33_L001_R1_001.fastq"
## [6] "ITS2-2020-6-16-H6_S33_L001_R2_001.fastq"list.files(path, pattern = "*.fastq")[1]## [1] "ITS2-2020-6-16-H1_S31_L001_R1_001.fastq"#R.utils::gunzip(list.files(path), remove=F)
R.utils::isGzipped(list.files(path, pattern = "*.fastq")[1]) # checking that the file is unzipped, FALSE = not gzipped## [1] FALSE# intstall R.utils
# library(R.utils)
# lapply(list.files(path, pattern = "*.gz"), FUN=gunzip, remove=F) # unzip all .gz files and don't remove compressed files
# I manually moved all compressed files into a new folder, leaving these unzipped files in the working directory for this script
# commenting out since I only need to unzip oncePrep raw sequence reads
Match forward and reverse reads by sample name. Pre-filter to remove reads with Ns.
Generate matched lists of fwd & rev reads with sample name
Forward and reverse fastq files have the format: ITS2_SAMPLENAME_SXXX_L001_R1_001.fastq and ITS2_SAMPLENAME_SXXX_L001_R2_001.fastq, respectively
For example: ITS2-2020-6-16-H1_S293_L001_R1_001.fastq is the forward reads of ITS2 sample 2020-06-16-H1
fnFs <- sort(list.files(path, pattern = "L001_R1_001.fastq", full.names = TRUE))
fnRs <- sort(list.files(path, pattern = "L001_R2_001.fastq", full.names = TRUE))
#string parsing may have to be altered in your own data if your file names have a different format.Pre-filter to remove reads with Ns
Ambiguous bases (Ns) in the sequencing reads makes accurate mapping of short primer sequences difficult. Here, remove reads with Ns, but perform no other filtering.
fnFs.filtN <- file.path(path, "filtN", basename(fnFs)) #create directory paths to contain N-filterd files in filtN/ subdirectory within path
fnRs.filtN <- file.path(path, "filtN", basename(fnRs))Now we can filter out whole sequences and trim parts of sequences based on their quality score. This function takes files from path /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2 and creates new files in filtN folder /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/filtN
filterAndTrim(fnFs, fnFs.filtN, fnRs, fnRs.filtN, maxN = 0, multithread = TRUE, matchIDs = TRUE, compress=FALSE) #eliminates sequences with more than 0 Ns; ## Some input samples had no reads pass the filter.#I had an issue with "Mismatched forward and reverse sequence files" but adding the matchID=T parameter fixed it; #I had an issue with the filtN files being compressed somehow so the cutadapt command couldn't read the files ("UnicodeDecodeError: 'utf-8' codec can't decode byte 0x8b in position 1: invalid start byte"), adding the compress = F parameter fixed it (("Or you could just gzip all your files at the beginning." - benjjneb))Check how much filtering affected read numbers
n=7
#before filterAndTrim
plotQualityProfile(fnFs[n:n]) #checking quality and number of FWD reads of nth sample
plotQualityProfile(fnRs[n:n]) #checking quality and number of REV reads of nth sample
#after filterAndTrim
plotQualityProfile(fnFs.filtN[n:n]) #checking quality and number of FWD reads of nth sample
plotQualityProfile(fnRs.filtN[n:n]) #checking quality and number of REV reads of nth sample
Not every sample made it through the pre-filter to remove reads with Ns
length(file.path(path, "filtN", basename(fnFs))) #length of "fnFs.filtN," created in chunk above (261)## [1] 262length(list.files(file.path(path, "filtN"), pattern = "L001_R1_001.fastq", full.names = TRUE)) #length of files actually written to the fnFs.filtN directories (###)## [1] 257Updating path names (after samples drop out)
# update directory, since not all samples made it thru the filter
fnFs.filtN <- file.path(path, "filtN", basename(list.files(file.path(path, "filtN"), pattern = "L001_R1_001.fastq", full.names = TRUE)))
fnRs.filtN <- file.path(path, "filtN", basename(list.files(file.path(path, "filtN"), pattern = "L001_R2_001.fastq", full.names = TRUE)))Identify primers in reads
Verify the presence and orientation of these primers
#ITS2 primers
FWD <- "ATGCGATACTTGGTGTGAAT" ## CHANGE ME to your forward primer sequence
REV <- "TCCTCCGCTTATTGATATGC" ## CHANGE ME...
#to ensure we have the right primers, and the correct orientation of the primers on the reads, we will verify the presence and orientation of these primers in the data
allOrients <- function(primer) {
# Create all orientations of the input sequence
require(Biostrings)
dna <- DNAString(primer) # The Biostrings works w/ DNAString objects rather than character vectors
orients <- c(Forward = dna, Complement = complement(dna), Reverse = reverse(dna),
RevComp = reverseComplement(dna))
return(sapply(orients, toString)) # Convert back to character vector
}
FWD.orients <- allOrients(FWD)
REV.orients <- allOrients(REV)
FWD.orients #all possible orientations of forward## Forward Complement Reverse
## "ATGCGATACTTGGTGTGAAT" "TACGCTATGAACCACACTTA" "TAAGTGTGGTTCATAGCGTA"
## RevComp
## "ATTCACACCAAGTATCGCAT"REV.orients #...and reverse primers## Forward Complement Reverse
## "TCCTCCGCTTATTGATATGC" "AGGAGGCGAATAACTATACG" "CGTATAGTTATTCGCCTCCT"
## RevComp
## "GCATATCAATAAGCGGAGGA"Count how many times primers appear in reads
We are now ready to count the number of times the primers appear in the forward and reverse read, while considering all possible primer orientations. Identifying and counting the primers on one set of paired end FASTQ files is sufficient, assuming all the files were created using the same library preparation, so we’ll just process the first sample.
primerHits <- function(primer, fn) {
# Counts number of reads in which the primer is found
nhits <- vcountPattern(primer, sread(readFastq(fn)), fixed = FALSE)
return(sum(nhits > 0))
}
#count of primer hits in the nth read
rbind(FWD.ForwardReads = sapply(FWD.orients, primerHits, fn = fnFs.filtN[[n]]),
FWD.ReverseReads = sapply(FWD.orients, primerHits, fn = fnRs.filtN[[n]]),
REV.ForwardReads = sapply(REV.orients, primerHits, fn = fnFs.filtN[[n]]),
REV.ReverseReads = sapply(REV.orients, primerHits, fn = fnRs.filtN[[n]]))## Forward Complement Reverse RevComp
## FWD.ForwardReads 53406 0 0 0
## FWD.ReverseReads 0 0 0 1
## REV.ForwardReads 0 0 0 1
## REV.ReverseReads 50849 0 0 0Note: Orientation mixups are a common trip-up. If, for example, the REV primer is matching the Reverse reads in its RevComp orientation, then replace REV with its reverse-complement orientation (REV <- REV.orient[[“RevComp”]]) before proceeding.
Remove primers from reads
These primers can be now removed using a specialized primer/adapter removal tool. Here, we use cutadapt for this purpose. Download, installation and usage instructions are available online: http://cutadapt.readthedocs.io/en/stable/index.html
#cutadapt <- "/Users/kelseyschoenemann/opt/anaconda3/envs/cutadaptenv/bin/cutadapt" #CHANGE ME to the cutadapt path on your local machine
cutadapt <- "/home/kls7sg/.local/bin/cutadapt" #for running on Rivanna HPC
system2(cutadapt, args = "--version") # Run shell commands from RIf the above command successfully executed, R has found cutadapt and you are ready to continue following along.
We now create output filenames for the cutadapt-ed files, and define the parameters we are going to give the cutadapt command. The critical parameters are the primers, and they need to be in the right orientation, i.e. the FWD primer should have been matching the forward-reads in its forward orientation, and the REV primer should have been matching the reverse-reads in its forward orientation.
Create directory with updated path names
path.cut <- file.path(path, "cutadapt"); if(!dir.exists(path.cut)) dir.create(path.cut) #create a new folder in the main directory called cutadapt
#/scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt
# fnFs.cut <- file.path(path.cut, basename(fnFs)) #old code #to place fwd reads w/o primers in the new cutadapt directory
# fnRs.cut <- file.path(path.cut, basename(fnRs)) #old code
length(file.path(path, basename(fnFs))) # 262 samples with F reads in original directory## [1] 262length(list.files(file.path(path, "filtN"), pattern = "L001_R1_001.fastq", full.names = TRUE)) # but only 257 samples passed the filtN filter (removing reads with Ns)## [1] 257# figuring out how to create/call directory paths with just retained samples
# basename(list.files(file.path(path, "filtN"), pattern = "L001_R1_001.fastq", full.names = TRUE))[1]
# file.path(path.cut, basename(list.files(file.path(path, "filtN"), pattern = "L001_R1_001.fastq", full.names = TRUE))[1])
# here's an updated directory that only includes destinations for samples/files that still exist
fnFs.cut <- file.path(path.cut, sort(basename(list.files(file.path(path, "filtN"), pattern = "R1_001.fastq", full.names = TRUE)))) #to place forward reads with primers cut (removed) in the new cutadapt directory
fnRs.cut <- file.path(path.cut, sort(basename(list.files(file.path(path, "filtN"), pattern = "R2_001.fastq", full.names = TRUE)))) #to place reverse reads with primers cut (removed) in the new cutadapt directoryRunning cutadapt
FWD.RC <- dada2:::rc(FWD) #generate reverse complement of fwd
REV.RC <- dada2:::rc(REV) #...and rev primers
R1.flags <- paste("-g", FWD, "-a", REV.RC) # To flag FWD and reverse-complement of REV for removal from forward reads (R1)
R2.flags <- paste("-G", REV, "-A", FWD.RC) # To flag REV and reverse-complement of FWD for removal from reverse reads (R2)
# Run Cutadapt to cut flagged sequences from input reads and save cut sequences to output folder
#Warning: A lot of output will be written to the console by cutadapt!
for(i in seq_along(fnFs)) {
system2(cutadapt, args = c(
R1.flags, R2.flags, "-n", 2, #-n 2 required to remove FWD & REV from reads
"-o", fnFs.cut[i], "-p", fnRs.cut[i], # output files
fnFs.filtN[i], fnRs.filtN[i]) # input files
)
}Count primers again
As a sanity check, we will count the presence of primers in the nth cutadapt-ed sample:
rbind(FWD.ForwardReads = sapply(FWD.orients, primerHits, fn = fnFs.cut[[n]]),
FWD.ReverseReads = sapply(FWD.orients, primerHits, fn = fnRs.cut[[n]]),
REV.ForwardReads = sapply(REV.orients, primerHits, fn = fnFs.cut[[n]]),
REV.ReverseReads = sapply(REV.orients, primerHits, fn = fnRs.cut[[n]]))## Forward Complement Reverse RevComp
## FWD.ForwardReads 0 0 0 0
## FWD.ReverseReads 0 0 0 0
## REV.ForwardReads 0 0 0 0
## REV.ReverseReads 0 0 0 0Success! Primers are no longer detected in the cutadapted reads. The primer-free sequence files are now ready to be analyzed through the DADA2 pipeline.
#Prep the pre-filtered & “cutadapted” sequence reads
Generate matched lists of fwd & rev reads with sample name
Create path names (all samples included)
#the only thing changing from last time is 'path' becomes 'path.cut'
#fnRs <- sort(list.files(path, pattern = "_2.fastq.gz", full.names = TRUE))
cutFs <- sort(list.files(path.cut, pattern = "L001_R1_001.fastq", full.names = TRUE))
cutRs <- sort(list.files(path.cut, pattern = "L001_R2_001.fastq", full.names = TRUE))Filter and trim “cutadapted” reads with filtering parameters
To store the output files of filtered reads as fastq.gz files, we’re creating another directory /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered
filtFs <- file.path(path.cut, "filtered", basename(cutFs))
filtRs <- file.path(path.cut, "filtered", basename(cutRs))#recall, the PRE-filter filter: filterAndTrim(fnFs, fnFs.filtN, fnRs, fnRs.filtN, maxN = 0, multithread = TRUE, matchIDs = T, compress=F) #eliminates sequences with more than 0 Ns
#NOW we filter for more stringent Quality Control
out <- filterAndTrim(cutFs, filtFs, cutRs, filtRs, maxN = 0, maxEE = c(2, 5), minLen = 50, rm.phix = TRUE, compress = TRUE, multithread = TRUE) #changed from default: maxEE=2,5## Some input samples had no reads pass the filter.head(out)## reads.in reads.out
## ITS2-2020-6-16-H1_S31_L001_R1_001.fastq 8 2
## ITS2-2020-6-16-H5_S32_L001_R1_001.fastq 5 3
## ITS2-2020-6-16-H6_S33_L001_R1_001.fastq 2 1
## ITS2-2020-6-17-H2_S34_L001_R1_001.fastq 14 7
## ITS2-2020-6-17-H4_S35_L001_R1_001.fastq 21 8
## ITS2-2020-6-17-H8_S36_L001_R1_001.fastq 7 5out.table<-as.data.frame(cbind(out,(out[,2]/out[,1])*100))
100-mean((out[,2]/out[,1])*100, na.rm=T) #loose __% of reads on average## [1] 49.00262For this dataset, we will use the following filtering parameters:
- maxN=0 #DADA2 requires sequences contain no Ns and Ns are already removed (this is the default setting)
- truncQ=2 #trims/truncates reads at the first instance of a bp with quality score =< 2 (this is the default setting)
- rm.phix=TRUE PhiX (FEE-ex) is a small virus with single-stranded DNA that you can spike in samples to use as control in sequencing #removes these reads in filtering
- maxEE=2,5 #sets the maximum number of “expected errors” allowed in a read.. c(2,5) sets the parameter for the F & R reads
- minLen=50 #sets the minimum bp length of reads #gets rid of spurious very low-length sequences
# testing effect of different parameter values
# out.sub <- filterAndTrim(head(cutFs, n=30L), head(filtFs, n=30L), head(cutRs, n=30L), head(filtRs, n=30L),
# maxEE = c(2, 5), minLen = 50, # modify maxEE, minLen here
# rm.phix = TRUE, compress = FALSE, multithread = TRUE)
# out.sub.table<-as.data.frame(cbind(out.sub,(out.sub[,2]/out.sub[,1])*100)) # calc perc reads remaining remaining
# summary(out.sub.table)
# 100-mean((out.sub[,2]/out.sub[,1])*100, na.rm=T) #loose __% of reads on average
#
# rm(out.sub, out.sub.table)Check how much filtering affected read quality profile and read numbers
n=n
#before filterAndTrim
plotQualityProfile(cutFs[n:n]) #checking quality and number of FWD reads of nth sample
#after filterAndTrim
plotQualityProfile(filtFs[n:n]) #checking quality and number of FWD reads of nth sample
Updating sample names (after samples drop out)
# updating sample names for "out"
length(rownames(as.data.frame(out)))## [1] 262 rownames(as.data.frame(out))## [1] "ITS2-2020-6-16-H1_S31_L001_R1_001.fastq"
## [2] "ITS2-2020-6-16-H5_S32_L001_R1_001.fastq"
## [3] "ITS2-2020-6-16-H6_S33_L001_R1_001.fastq"
## [4] "ITS2-2020-6-17-H2_S34_L001_R1_001.fastq"
## [5] "ITS2-2020-6-17-H4_S35_L001_R1_001.fastq"
## [6] "ITS2-2020-6-17-H8_S36_L001_R1_001.fastq"
## [7] "ITS2-2020-6-18-H3_S37_L001_R1_001.fastq"
## [8] "ITS2-2020-6-18-H7_S38_L001_R1_001.fastq"
## [9] "ITS2-2020-6-18-H9_S39_L001_R1_001.fastq"
## [10] "ITS2-2020-6-3-H1_S40_L001_R1_001.fastq"
## [11] "ITS2-2020-6-3-H5_S41_L001_R1_001.fastq"
## [12] "ITS2-2020-6-3-H6_S42_L001_R1_001.fastq"
## [13] "ITS2-2020-6-30-H1_S43_L001_R1_001.fastq"
## [14] "ITS2-2020-6-30-H5_S44_L001_R1_001.fastq"
## [15] "ITS2-2020-6-30-H6_S45_L001_R1_001.fastq"
## [16] "ITS2-2020-6-4-H2_S46_L001_R1_001.fastq"
## [17] "ITS2-2020-6-4-H4_S47_L001_R1_001.fastq"
## [18] "ITS2-2020-6-4-H8_S48_L001_R1_001.fastq"
## [19] "ITS2-2020-6-5-H3_S49_L001_R1_001.fastq"
## [20] "ITS2-2020-6-5-H7_S50_L001_R1_001.fastq"
## [21] "ITS2-2020-6-5-H9_S51_L001_R1_001.fastq"
## [22] "ITS2-2020-7-1-H2_S52_L001_R1_001.fastq"
## [23] "ITS2-2020-7-1-H4_S53_L001_R1_001.fastq"
## [24] "ITS2-2020-7-1-H8_S54_L001_R1_001.fastq"
## [25] "ITS2-2020-7-14-H1_S55_L001_R1_001.fastq"
## [26] "ITS2-2020-7-14-H5_S56_L001_R1_001.fastq"
## [27] "ITS2-2020-7-14-H6_S57_L001_R1_001.fastq"
## [28] "ITS2-2020-7-15-H2_S58_L001_R1_001.fastq"
## [29] "ITS2-2020-7-15-H4_S59_L001_R1_001.fastq"
## [30] "ITS2-2020-7-15-H8_S60_L001_R1_001.fastq"
## [31] "ITS2-2020-7-16-H3_S61_L001_R1_001.fastq"
## [32] "ITS2-2020-7-16-H7_S62_L001_R1_001.fastq"
## [33] "ITS2-2020-7-16-H9_S63_L001_R1_001.fastq"
## [34] "ITS2-2020-7-2-H3_S64_L001_R1_001.fastq"
## [35] "ITS2-2020-7-2-H7_S65_L001_R1_001.fastq"
## [36] "ITS2-2020-7-2-H9_S66_L001_R1_001.fastq"
## [37] "ITS2-2021-6-13-H1_S67_L001_R1_001.fastq"
## [38] "ITS2-2021-6-13-H3_S68_L001_R1_001.fastq"
## [39] "ITS2-2021-6-14-H11_S69_L001_R1_001.fastq"
## [40] "ITS2-2021-6-14-H6_S70_L001_R1_001.fastq"
## [41] "ITS2-2021-6-14-H7_S71_L001_R1_001.fastq"
## [42] "ITS2-2021-6-15-H8_S72_L001_R1_001.fastq"
## [43] "ITS2-2021-6-21-H10_S73_L001_R1_001.fastq"
## [44] "ITS2-2021-6-21-H12_S74_L001_R1_001.fastq"
## [45] "ITS2-2021-6-21-H9_S75_L001_R1_001.fastq"
## [46] "ITS2-2021-6-27-H21_S76_L001_R1_001.fastq"
## [47] "ITS2-2021-6-27-H22_S77_L001_R1_001.fastq"
## [48] "ITS2-2021-6-27-H27_S78_L001_R1_001.fastq"
## [49] "ITS2-2021-6-28-H25_S79_L001_R1_001.fastq"
## [50] "ITS2-2021-6-28-H26_S80_L001_R1_001.fastq"
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## [52] "ITS2-2021-6-29-H17_S82_L001_R1_001.fastq"
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## [55] "ITS2-2021-6-4-H21_S85_L001_R1_001.fastq"
## [56] "ITS2-2021-6-4-H22_S86_L001_R1_001.fastq"
## [57] "ITS2-2021-6-4-H27_S87_L001_R1_001.fastq"
## [58] "ITS2-2021-6-5-H18_S88_L001_R1_001.fastq"
## [59] "ITS2-2021-6-5-H25_S89_L001_R1_001.fastq"
## [60] "ITS2-2021-6-5-H26_S90_L001_R1_001.fastq"
## [61] "ITS2-2021-6-6-H17_S91_L001_R1_001.fastq"
## [62] "ITS2-2021-6-6-H24_S92_L001_R1_001.fastq"
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## [64] "ITS2-2021-7-14-H10_S94_L001_R1_001.fastq"
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## [67] "ITS2-2021-7-21-H25_S97_L001_R1_001.fastq"
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## [69] "ITS2-2021-7-21-H28_S99_L001_R1_001.fastq"
## [70] "ITS2-2021-7-6-H11_S100_L001_R1_001.fastq"
## [71] "ITS2-2021-7-6-H30_S101_L001_R1_001.fastq"
## [72] "ITS2-2021-7-6-H6_S102_L001_R1_001.fastq"
## [73] "ITS2-2021-7-7-H4_S103_L001_R1_001.fastq"
## [74] "ITS2-2021-7-7-H8_S104_L001_R1_001.fastq"
## [75] "ITS2-2021-7-8-H3_S105_L001_R1_001.fastq"
## [76] "ITS2-2023-6-12-H3_S106_L001_R1_001.fastq"
## [77] "ITS2-2023-6-12-H5_S107_L001_R1_001.fastq"
## [78] "ITS2-2023-6-12-H7_S108_L001_R1_001.fastq"
## [79] "ITS2-2023-6-13-H6_S109_L001_R1_001.fastq"
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## [85] "ITS2-2023-6-16-H5_S115_L001_R1_001.fastq"
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## [87] "ITS2-2023-6-24-H8_S117_L001_R1_001.fastq"
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## [90] "ITS2-2023-6-26-H1_S120_L001_R1_001.fastq"
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## [92] "ITS2-2023-6-27-H3_S122_L001_R1_001.fastq"
## [93] "ITS2-2023-6-27-H5_S123_L001_R1_001.fastq"
## [94] "ITS2-2023-6-8-H1_S124_L001_R1_001.fastq"
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## [103] "ITS2-2023-7-18-H7_S133_L001_R1_001.fastq"
## [104] "ITS2-2023-7-29-H5_S134_L001_R1_001.fastq"
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## [107] "ITS2-2023-7-30-H9_S137_L001_R1_001.fastq"
## [108] "ITS2-2023-7-5-H1_S138_L001_R1_001.fastq"
## [109] "ITS2-2023-7-5-H2_S139_L001_R1_001.fastq"
## [110] "ITS2-2023-7-5-H4_S140_L001_R1_001.fastq"
## [111] "ITS2-2023-7-6-H6_S141_L001_R1_001.fastq"
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## [113] "ITS2-2023-7-6-H9_S143_L001_R1_001.fastq"
## [114] "ITS2-2023-7-8-H3_S144_L001_R1_001.fastq"
## [115] "ITS2-2023-7-8-H5_S145_L001_R1_001.fastq"
## [116] "ITS2-2023-7-8-H7_S146_L001_R1_001.fastq"
## [117] "ITS2-2023-8-4-H2_S147_L001_R1_001.fastq"
## [118] "ITS2-2023-8-4-H5_S148_L001_R1_001.fastq"
## [119] "ITS2-2023-8-4-H6_S149_L001_R1_001.fastq"
## [120] "ITS2-2023-8-4-H7_S150_L001_R1_001.fastq"
## [121] "ITS2-2023-8-4-H8_S151_L001_R1_001.fastq"
## [122] "ITS2-2023-8-4-H9_S152_L001_R1_001.fastq"
## [123] "ITS2-Ba001_S153_L001_R1_001.fastq"
## [124] "ITS2-Ba002_S154_L001_R1_001.fastq"
## [125] "ITS2-Ba003_S155_L001_R1_001.fastq"
## [126] "ITS2-Bb001_S156_L001_R1_001.fastq"
## [127] "ITS2-Bb002_S157_L001_R1_001.fastq"
## [128] "ITS2-Bb003_S158_L001_R1_001.fastq"
## [129] "ITS2-Bb004_S159_L001_R1_001.fastq"
## [130] "ITS2-Bb005_S160_L001_R1_001.fastq"
## [131] "ITS2-Bb007_S161_L001_R1_001.fastq"
## [132] "ITS2-Bb008_S162_L001_R1_001.fastq"
## [133] "ITS2-Bb009_S163_L001_R1_001.fastq"
## [134] "ITS2-Bb010_S164_L001_R1_001.fastq"
## [135] "ITS2-Bb011_S165_L001_R1_001.fastq"
## [136] "ITS2-Bb012_S166_L001_R1_001.fastq"
## [137] "ITS2-Bb013_S167_L001_R1_001.fastq"
## [138] "ITS2-Bb014_S168_L001_R1_001.fastq"
## [139] "ITS2-Bb015_S169_L001_R1_001.fastq"
## [140] "ITS2-Bb016_S170_L001_R1_001.fastq"
## [141] "ITS2-Bb017_S171_L001_R1_001.fastq"
## [142] "ITS2-Bb018_S172_L001_R1_001.fastq"
## [143] "ITS2-Bb019_S173_L001_R1_001.fastq"
## [144] "ITS2-Bb020_S174_L001_R1_001.fastq"
## [145] "ITS2-Bb021_S175_L001_R1_001.fastq"
## [146] "ITS2-Bb022_S176_L001_R1_001.fastq"
## [147] "ITS2-Bb023_S177_L001_R1_001.fastq"
## [148] "ITS2-Bb024_S178_L001_R1_001.fastq"
## [149] "ITS2-Bb025_S179_L001_R1_001.fastq"
## [150] "ITS2-Bf001_S180_L001_R1_001.fastq"
## [151] "ITS2-Bf002_S181_L001_R1_001.fastq"
## [152] "ITS2-Bf003_S182_L001_R1_001.fastq"
## [153] "ITS2-Bf004_S183_L001_R1_001.fastq"
## [154] "ITS2-Bg001_S184_L001_R1_001.fastq"
## [155] "ITS2-Bg002_S185_L001_R1_001.fastq"
## [156] "ITS2-Bg003_S186_L001_R1_001.fastq"
## [157] "ITS2-Bg004_S187_L001_R1_001.fastq"
## [158] "ITS2-Bg005_S188_L001_R1_001.fastq"
## [159] "ITS2-Bg006_S189_L001_R1_001.fastq"
## [160] "ITS2-Bg007_S190_L001_R1_001.fastq"
## [161] "ITS2-Bg008_S191_L001_R1_001.fastq"
## [162] "ITS2-Bg009_S192_L001_R1_001.fastq"
## [163] "ITS2-Bg010_S193_L001_R1_001.fastq"
## [164] "ITS2-Bg011_S194_L001_R1_001.fastq"
## [165] "ITS2-Bg012_S195_L001_R1_001.fastq"
## [166] "ITS2-Bg013_S196_L001_R1_001.fastq"
## [167] "ITS2-Bg014_S197_L001_R1_001.fastq"
## [168] "ITS2-Bg015_S198_L001_R1_001.fastq"
## [169] "ITS2-Bg016_S199_L001_R1_001.fastq"
## [170] "ITS2-Bg017_S200_L001_R1_001.fastq"
## [171] "ITS2-Bg018_S201_L001_R1_001.fastq"
## [172] "ITS2-Bg019_S202_L001_R1_001.fastq"
## [173] "ITS2-Bi001_S203_L001_R1_001.fastq"
## [174] "ITS2-Bi002_S204_L001_R1_001.fastq"
## [175] "ITS2-Bi003_S205_L001_R1_001.fastq"
## [176] "ITS2-Bi004_S206_L001_R1_001.fastq"
## [177] "ITS2-Bi005_S207_L001_R1_001.fastq"
## [178] "ITS2-Bi006_S208_L001_R1_001.fastq"
## [179] "ITS2-Bi007_S209_L001_R1_001.fastq"
## [180] "ITS2-CKC0001_S210_L001_R1_001.fastq"
## [181] "ITS2-ESE0004_S211_L001_R1_001.fastq"
## [182] "ITS2-ext-neg-ctrl-20230909_S212_L001_R1_001.fastq"
## [183] "ITS2-ext-neg-ctrl-20230923_S213_L001_R1_001.fastq"
## [184] "ITS2-ext-neg-ctrl-20230924_S214_L001_R1_001.fastq"
## [185] "ITS2-ext-neg-ctrl-20231007_S215_L001_R1_001.fastq"
## [186] "ITS2-ext-neg-ctrl-20231008_S216_L001_R1_001.fastq"
## [187] "ITS2-ext-neg-ctrl-20231009_S217_L001_R1_001.fastq"
## [188] "ITS2-ext-neg-ctrl-2024220A_S218_L001_R1_001.fastq"
## [189] "ITS2-ext-neg-ctrl-2024220B_S219_L001_R1_001.fastq"
## [190] "ITS2-ext-neg-ctrl-2024221A_S220_L001_R1_001.fastq"
## [191] "ITS2-ext-neg-ctrl-2024221B_S221_L001_R1_001.fastq"
## [192] "ITS2-ext-neg-ctrl-2024222A_S222_L001_R1_001.fastq"
## [193] "ITS2-ext-neg-ctrl-2024222B_S223_L001_R1_001.fastq"
## [194] "ITS2-ext-neg-ctrl-2024312A_S224_L001_R1_001.fastq"
## [195] "ITS2-ext-neg-ctrl-2024312B_S225_L001_R1_001.fastq"
## [196] "ITS2-ext-neg-ctrl-2024314A_S226_L001_R1_001.fastq"
## [197] "ITS2-ext-neg-ctrl-2024314B_S227_L001_R1_001.fastq"
## [198] "ITS2-ext-neg-ctrl-2024319_S228_L001_R1_001.fastq"
## [199] "ITS2-ext-neg-ctrl-2024320_S229_L001_R1_001.fastq"
## [200] "ITS2-KLS0007_S230_L001_R1_001.fastq"
## [201] "ITS2-KLS0027_S232_L001_R1_001.fastq"
## [202] "ITS2-KLS0044_S233_L001_R1_001.fastq"
## [203] "ITS2-KLS0045_S234_L001_R1_001.fastq"
## [204] "ITS2-KLS0052_S235_L001_R1_001.fastq"
## [205] "ITS2-KLS0054_S236_L001_R1_001.fastq"
## [206] "ITS2-KLS0055_S237_L001_R1_001.fastq"
## [207] "ITS2-KLS0071_S238_L001_R1_001.fastq"
## [208] "ITS2-KLS0095_S239_L001_R1_001.fastq"
## [209] "ITS2-KLS0096_S240_L001_R1_001.fastq"
## [210] "ITS2-KLS0105_S241_L001_R1_001.fastq"
## [211] "ITS2-KLS0106_S242_L001_R1_001.fastq"
## [212] "ITS2-KLS0119_S243_L001_R1_001.fastq"
## [213] "ITS2-KLS0134_S244_L001_R1_001.fastq"
## [214] "ITS2-KLS0135_S245_L001_R1_001.fastq"
## [215] "ITS2-KLS0136_S246_L001_R1_001.fastq"
## [216] "ITS2-KLS0137_S247_L001_R1_001.fastq"
## [217] "ITS2-KLS0138_S248_L001_R1_001.fastq"
## [218] "ITS2-KLS0139_S249_L001_R1_001.fastq"
## [219] "ITS2-KLS0150_S250_L001_R1_001.fastq"
## [220] "ITS2-KLS0153_S251_L001_R1_001.fastq"
## [221] "ITS2-KLS0155_S252_L001_R1_001.fastq"
## [222] "ITS2-KLS0156_S253_L001_R1_001.fastq"
## [223] "ITS2-KLS0159_S254_L001_R1_001.fastq"
## [224] "ITS2-KLS0163_S255_L001_R1_001.fastq"
## [225] "ITS2-KLS0165_S256_L001_R1_001.fastq"
## [226] "ITS2-KLS0167_S257_L001_R1_001.fastq"
## [227] "ITS2-KLS0168_S258_L001_R1_001.fastq"
## [228] "ITS2-KLS0169_S259_L001_R1_001.fastq"
## [229] "ITS2-KLS0170_S260_L001_R1_001.fastq"
## [230] "ITS2-KLS0200_S261_L001_R1_001.fastq"
## [231] "ITS2-KLS0201_S262_L001_R1_001.fastq"
## [232] "ITS2-KLS0205_S263_L001_R1_001.fastq"
## [233] "ITS2-KLS0209_S264_L001_R1_001.fastq"
## [234] "ITS2-KLS0221_S265_L001_R1_001.fastq"
## [235] "ITS2-KLS0224_S266_L001_R1_001.fastq"
## [236] "ITS2-KLS0225_S267_L001_R1_001.fastq"
## [237] "ITS2-KLS0227_S268_L001_R1_001.fastq"
## [238] "ITS2-KLS0241_S269_L001_R1_001.fastq"
## [239] "ITS2-KLS0244_S270_L001_R1_001.fastq"
## [240] "ITS2-KLS0246_S271_L001_R1_001.fastq"
## [241] "ITS2-KLS0248_S272_L001_R1_001.fastq"
## [242] "ITS2-KLS0253_S273_L001_R1_001.fastq"
## [243] "ITS2-KLS0254_S274_L001_R1_001.fastq"
## [244] "ITS2-KLS0256_S231_L001_R1_001.fastq"
## [245] "ITS2-KLS0259_S275_L001_R1_001.fastq"
## [246] "ITS2-KLS0263_S276_L001_R1_001.fastq"
## [247] "ITS2-KLS0266_S277_L001_R1_001.fastq"
## [248] "ITS2-KLS0272_S278_L001_R1_001.fastq"
## [249] "ITS2-pcr-its2-neg-ctrl-20231021-20231119_S279_L001_R1_001.fastq"
## [250] "ITS2-pcr-its2-neg-ctrl-20231022-20231120_S280_L001_R1_001.fastq"
## [251] "ITS2-pcr-its2-neg-ctrl-20231023_S281_L001_R1_001.fastq"
## [252] "ITS2-pcr-its2-neg-ctrl-20240411_S282_L001_R1_001.fastq"
## [253] "ITS2-pcr-its2-neg-ctrl-20240416_S283_L001_R1_001.fastq"
## [254] "ITS2-pcr-its2-neg-ctrl-20240417_S284_L001_R1_001.fastq"
## [255] "ITS2-pcr-its2-neg-ctrl-20240418A_S285_L001_R1_001.fastq"
## [256] "ITS2-pcr-its2-neg-ctrl-20240418B_S286_L001_R1_001.fastq"
## [257] "ITS2-pcr-its2-neg-ctrl-20240517_S287_L001_R1_001.fastq"
## [258] "ITS2-pcr-its2-neg-ctrl-20240524_S288_L001_R1_001.fastq"
## [259] "ITS2-pcr-its2-neg-ctrl-Saskia-20240411_S289_L001_R1_001.fastq"
## [260] "ITS2-SCA0009_S290_L001_R1_001.fastq"
## [261] "ITS2-SCA0010_S291_L001_R1_001.fastq"
## [262] "ITS2-SCA0013_S292_L001_R1_001.fastq" strsplit(rownames(as.data.frame(out)), "_S")## [[1]]
## [1] "ITS2-2020-6-16-H1" "31_L001_R1_001.fastq"
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## [1] "ITS2-2020-6-16-H5" "32_L001_R1_001.fastq"
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## [1] "ITS2-2020-6-18-H9" "39_L001_R1_001.fastq"
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## [1] "ITS2-2020-6-3-H1" "40_L001_R1_001.fastq"
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## [1] "ITS2-2020-6-3-H6" "42_L001_R1_001.fastq"
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## [1] "ITS2-2020-6-30-H1" "43_L001_R1_001.fastq"
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## [1] "ITS2-2020-6-30-H5" "44_L001_R1_001.fastq"
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## [1] "ITS2-2020-6-30-H6" "45_L001_R1_001.fastq"
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## [1] "ITS2-2020-6-4-H2" "46_L001_R1_001.fastq"
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## [1] "ITS2-2020-6-4-H4" "47_L001_R1_001.fastq"
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## [1] "ITS2-2020-6-4-H8" "48_L001_R1_001.fastq"
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## [1] "ITS2-2020-6-5-H3" "49_L001_R1_001.fastq"
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## [1] "ITS2-2020-6-5-H7" "50_L001_R1_001.fastq"
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## [1] "ITS2-2020-6-5-H9" "51_L001_R1_001.fastq"
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## [1] "ITS2-2020-7-1-H2" "52_L001_R1_001.fastq"
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## [1] "ITS2-2020-7-1-H4" "53_L001_R1_001.fastq"
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## [1] "ITS2-2020-7-14-H1" "55_L001_R1_001.fastq"
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## [1] "ITS2-2020-7-14-H5" "56_L001_R1_001.fastq"
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## [1] "ITS2-2020-7-14-H6" "57_L001_R1_001.fastq"
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## [1] "ITS2-2020-7-15-H2" "58_L001_R1_001.fastq"
##
## [[29]]
## [1] "ITS2-2020-7-15-H4" "59_L001_R1_001.fastq"
##
## [[30]]
## [1] "ITS2-2020-7-15-H8" "60_L001_R1_001.fastq"
##
## [[31]]
## [1] "ITS2-2020-7-16-H3" "61_L001_R1_001.fastq"
##
## [[32]]
## [1] "ITS2-2020-7-16-H7" "62_L001_R1_001.fastq"
##
## [[33]]
## [1] "ITS2-2020-7-16-H9" "63_L001_R1_001.fastq"
##
## [[34]]
## [1] "ITS2-2020-7-2-H3" "64_L001_R1_001.fastq"
##
## [[35]]
## [1] "ITS2-2020-7-2-H7" "65_L001_R1_001.fastq"
##
## [[36]]
## [1] "ITS2-2020-7-2-H9" "66_L001_R1_001.fastq"
##
## [[37]]
## [1] "ITS2-2021-6-13-H1" "67_L001_R1_001.fastq"
##
## [[38]]
## [1] "ITS2-2021-6-13-H3" "68_L001_R1_001.fastq"
##
## [[39]]
## [1] "ITS2-2021-6-14-H11" "69_L001_R1_001.fastq"
##
## [[40]]
## [1] "ITS2-2021-6-14-H6" "70_L001_R1_001.fastq"
##
## [[41]]
## [1] "ITS2-2021-6-14-H7" "71_L001_R1_001.fastq"
##
## [[42]]
## [1] "ITS2-2021-6-15-H8" "72_L001_R1_001.fastq"
##
## [[43]]
## [1] "ITS2-2021-6-21-H10" "73_L001_R1_001.fastq"
##
## [[44]]
## [1] "ITS2-2021-6-21-H12" "74_L001_R1_001.fastq"
##
## [[45]]
## [1] "ITS2-2021-6-21-H9" "75_L001_R1_001.fastq"
##
## [[46]]
## [1] "ITS2-2021-6-27-H21" "76_L001_R1_001.fastq"
##
## [[47]]
## [1] "ITS2-2021-6-27-H22" "77_L001_R1_001.fastq"
##
## [[48]]
## [1] "ITS2-2021-6-27-H27" "78_L001_R1_001.fastq"
##
## [[49]]
## [1] "ITS2-2021-6-28-H25" "79_L001_R1_001.fastq"
##
## [[50]]
## [1] "ITS2-2021-6-28-H26" "80_L001_R1_001.fastq"
##
## [[51]]
## [1] "ITS2-2021-6-28-H28" "81_L001_R1_001.fastq"
##
## [[52]]
## [1] "ITS2-2021-6-29-H17" "82_L001_R1_001.fastq"
##
## [[53]]
## [1] "ITS2-2021-6-29-H23" "83_L001_R1_001.fastq"
##
## [[54]]
## [1] "ITS2-2021-6-29-H24" "84_L001_R1_001.fastq"
##
## [[55]]
## [1] "ITS2-2021-6-4-H21" "85_L001_R1_001.fastq"
##
## [[56]]
## [1] "ITS2-2021-6-4-H22" "86_L001_R1_001.fastq"
##
## [[57]]
## [1] "ITS2-2021-6-4-H27" "87_L001_R1_001.fastq"
##
## [[58]]
## [1] "ITS2-2021-6-5-H18" "88_L001_R1_001.fastq"
##
## [[59]]
## [1] "ITS2-2021-6-5-H25" "89_L001_R1_001.fastq"
##
## [[60]]
## [1] "ITS2-2021-6-5-H26" "90_L001_R1_001.fastq"
##
## [[61]]
## [1] "ITS2-2021-6-6-H17" "91_L001_R1_001.fastq"
##
## [[62]]
## [1] "ITS2-2021-6-6-H24" "92_L001_R1_001.fastq"
##
## [[63]]
## [1] "ITS2-2021-6-7-H23" "93_L001_R1_001.fastq"
##
## [[64]]
## [1] "ITS2-2021-7-14-H10" "94_L001_R1_001.fastq"
##
## [[65]]
## [1] "ITS2-2021-7-14-H12" "95_L001_R1_001.fastq"
##
## [[66]]
## [1] "ITS2-2021-7-20-H27" "96_L001_R1_001.fastq"
##
## [[67]]
## [1] "ITS2-2021-7-21-H25" "97_L001_R1_001.fastq"
##
## [[68]]
## [1] "ITS2-2021-7-21-H26" "98_L001_R1_001.fastq"
##
## [[69]]
## [1] "ITS2-2021-7-21-H28" "99_L001_R1_001.fastq"
##
## [[70]]
## [1] "ITS2-2021-7-6-H11" "100_L001_R1_001.fastq"
##
## [[71]]
## [1] "ITS2-2021-7-6-H30" "101_L001_R1_001.fastq"
##
## [[72]]
## [1] "ITS2-2021-7-6-H6" "102_L001_R1_001.fastq"
##
## [[73]]
## [1] "ITS2-2021-7-7-H4" "103_L001_R1_001.fastq"
##
## [[74]]
## [1] "ITS2-2021-7-7-H8" "104_L001_R1_001.fastq"
##
## [[75]]
## [1] "ITS2-2021-7-8-H3" "105_L001_R1_001.fastq"
##
## [[76]]
## [1] "ITS2-2023-6-12-H3" "106_L001_R1_001.fastq"
##
## [[77]]
## [1] "ITS2-2023-6-12-H5" "107_L001_R1_001.fastq"
##
## [[78]]
## [1] "ITS2-2023-6-12-H7" "108_L001_R1_001.fastq"
##
## [[79]]
## [1] "ITS2-2023-6-13-H6" "109_L001_R1_001.fastq"
##
## [[80]]
## [1] "ITS2-2023-6-13-H8" "110_L001_R1_001.fastq"
##
## [[81]]
## [1] "ITS2-2023-6-13-H9" "111_L001_R1_001.fastq"
##
## [[82]]
## [1] "ITS2-2023-6-14-H3" "112_L001_R1_001.fastq"
##
## [[83]]
## [1] "ITS2-2023-6-14-H7" "113_L001_R1_001.fastq"
##
## [[84]]
## [1] "ITS2-2023-6-14-H9" "114_L001_R1_001.fastq"
##
## [[85]]
## [1] "ITS2-2023-6-16-H5" "115_L001_R1_001.fastq"
##
## [[86]]
## [1] "ITS2-2023-6-24-H6" "116_L001_R1_001.fastq"
##
## [[87]]
## [1] "ITS2-2023-6-24-H8" "117_L001_R1_001.fastq"
##
## [[88]]
## [1] "ITS2-2023-6-25-H2" "118_L001_R1_001.fastq"
##
## [[89]]
## [1] "ITS2-2023-6-25-H4" "119_L001_R1_001.fastq"
##
## [[90]]
## [1] "ITS2-2023-6-26-H1" "120_L001_R1_001.fastq"
##
## [[91]]
## [1] "ITS2-2023-6-26-H7" "121_L001_R1_001.fastq"
##
## [[92]]
## [1] "ITS2-2023-6-27-H3" "122_L001_R1_001.fastq"
##
## [[93]]
## [1] "ITS2-2023-6-27-H5" "123_L001_R1_001.fastq"
##
## [[94]]
## [1] "ITS2-2023-6-8-H1" "124_L001_R1_001.fastq"
##
## [[95]]
## [1] "ITS2-2023-6-8-H2" "125_L001_R1_001.fastq"
##
## [[96]]
## [1] "ITS2-2023-6-8-H4" "126_L001_R1_001.fastq"
##
## [[97]]
## [1] "ITS2-2023-6-9-H2" "127_L001_R1_001.fastq"
##
## [[98]]
## [1] "ITS2-2023-6-9-H4" "128_L001_R1_001.fastq"
##
## [[99]]
## [1] "ITS2-2023-7-15-H6" "129_L001_R1_001.fastq"
##
## [[100]]
## [1] "ITS2-2023-7-16-H4" "130_L001_R1_001.fastq"
##
## [[101]]
## [1] "ITS2-2023-7-17-H1" "131_L001_R1_001.fastq"
##
## [[102]]
## [1] "ITS2-2023-7-18-H3" "132_L001_R1_001.fastq"
##
## [[103]]
## [1] "ITS2-2023-7-18-H7" "133_L001_R1_001.fastq"
##
## [[104]]
## [1] "ITS2-2023-7-29-H5" "134_L001_R1_001.fastq"
##
## [[105]]
## [1] "ITS2-2023-7-29-H7" "135_L001_R1_001.fastq"
##
## [[106]]
## [1] "ITS2-2023-7-30-H8" "136_L001_R1_001.fastq"
##
## [[107]]
## [1] "ITS2-2023-7-30-H9" "137_L001_R1_001.fastq"
##
## [[108]]
## [1] "ITS2-2023-7-5-H1" "138_L001_R1_001.fastq"
##
## [[109]]
## [1] "ITS2-2023-7-5-H2" "139_L001_R1_001.fastq"
##
## [[110]]
## [1] "ITS2-2023-7-5-H4" "140_L001_R1_001.fastq"
##
## [[111]]
## [1] "ITS2-2023-7-6-H6" "141_L001_R1_001.fastq"
##
## [[112]]
## [1] "ITS2-2023-7-6-H8" "142_L001_R1_001.fastq"
##
## [[113]]
## [1] "ITS2-2023-7-6-H9" "143_L001_R1_001.fastq"
##
## [[114]]
## [1] "ITS2-2023-7-8-H3" "144_L001_R1_001.fastq"
##
## [[115]]
## [1] "ITS2-2023-7-8-H5" "145_L001_R1_001.fastq"
##
## [[116]]
## [1] "ITS2-2023-7-8-H7" "146_L001_R1_001.fastq"
##
## [[117]]
## [1] "ITS2-2023-8-4-H2" "147_L001_R1_001.fastq"
##
## [[118]]
## [1] "ITS2-2023-8-4-H5" "148_L001_R1_001.fastq"
##
## [[119]]
## [1] "ITS2-2023-8-4-H6" "149_L001_R1_001.fastq"
##
## [[120]]
## [1] "ITS2-2023-8-4-H7" "150_L001_R1_001.fastq"
##
## [[121]]
## [1] "ITS2-2023-8-4-H8" "151_L001_R1_001.fastq"
##
## [[122]]
## [1] "ITS2-2023-8-4-H9" "152_L001_R1_001.fastq"
##
## [[123]]
## [1] "ITS2-Ba001" "153_L001_R1_001.fastq"
##
## [[124]]
## [1] "ITS2-Ba002" "154_L001_R1_001.fastq"
##
## [[125]]
## [1] "ITS2-Ba003" "155_L001_R1_001.fastq"
##
## [[126]]
## [1] "ITS2-Bb001" "156_L001_R1_001.fastq"
##
## [[127]]
## [1] "ITS2-Bb002" "157_L001_R1_001.fastq"
##
## [[128]]
## [1] "ITS2-Bb003" "158_L001_R1_001.fastq"
##
## [[129]]
## [1] "ITS2-Bb004" "159_L001_R1_001.fastq"
##
## [[130]]
## [1] "ITS2-Bb005" "160_L001_R1_001.fastq"
##
## [[131]]
## [1] "ITS2-Bb007" "161_L001_R1_001.fastq"
##
## [[132]]
## [1] "ITS2-Bb008" "162_L001_R1_001.fastq"
##
## [[133]]
## [1] "ITS2-Bb009" "163_L001_R1_001.fastq"
##
## [[134]]
## [1] "ITS2-Bb010" "164_L001_R1_001.fastq"
##
## [[135]]
## [1] "ITS2-Bb011" "165_L001_R1_001.fastq"
##
## [[136]]
## [1] "ITS2-Bb012" "166_L001_R1_001.fastq"
##
## [[137]]
## [1] "ITS2-Bb013" "167_L001_R1_001.fastq"
##
## [[138]]
## [1] "ITS2-Bb014" "168_L001_R1_001.fastq"
##
## [[139]]
## [1] "ITS2-Bb015" "169_L001_R1_001.fastq"
##
## [[140]]
## [1] "ITS2-Bb016" "170_L001_R1_001.fastq"
##
## [[141]]
## [1] "ITS2-Bb017" "171_L001_R1_001.fastq"
##
## [[142]]
## [1] "ITS2-Bb018" "172_L001_R1_001.fastq"
##
## [[143]]
## [1] "ITS2-Bb019" "173_L001_R1_001.fastq"
##
## [[144]]
## [1] "ITS2-Bb020" "174_L001_R1_001.fastq"
##
## [[145]]
## [1] "ITS2-Bb021" "175_L001_R1_001.fastq"
##
## [[146]]
## [1] "ITS2-Bb022" "176_L001_R1_001.fastq"
##
## [[147]]
## [1] "ITS2-Bb023" "177_L001_R1_001.fastq"
##
## [[148]]
## [1] "ITS2-Bb024" "178_L001_R1_001.fastq"
##
## [[149]]
## [1] "ITS2-Bb025" "179_L001_R1_001.fastq"
##
## [[150]]
## [1] "ITS2-Bf001" "180_L001_R1_001.fastq"
##
## [[151]]
## [1] "ITS2-Bf002" "181_L001_R1_001.fastq"
##
## [[152]]
## [1] "ITS2-Bf003" "182_L001_R1_001.fastq"
##
## [[153]]
## [1] "ITS2-Bf004" "183_L001_R1_001.fastq"
##
## [[154]]
## [1] "ITS2-Bg001" "184_L001_R1_001.fastq"
##
## [[155]]
## [1] "ITS2-Bg002" "185_L001_R1_001.fastq"
##
## [[156]]
## [1] "ITS2-Bg003" "186_L001_R1_001.fastq"
##
## [[157]]
## [1] "ITS2-Bg004" "187_L001_R1_001.fastq"
##
## [[158]]
## [1] "ITS2-Bg005" "188_L001_R1_001.fastq"
##
## [[159]]
## [1] "ITS2-Bg006" "189_L001_R1_001.fastq"
##
## [[160]]
## [1] "ITS2-Bg007" "190_L001_R1_001.fastq"
##
## [[161]]
## [1] "ITS2-Bg008" "191_L001_R1_001.fastq"
##
## [[162]]
## [1] "ITS2-Bg009" "192_L001_R1_001.fastq"
##
## [[163]]
## [1] "ITS2-Bg010" "193_L001_R1_001.fastq"
##
## [[164]]
## [1] "ITS2-Bg011" "194_L001_R1_001.fastq"
##
## [[165]]
## [1] "ITS2-Bg012" "195_L001_R1_001.fastq"
##
## [[166]]
## [1] "ITS2-Bg013" "196_L001_R1_001.fastq"
##
## [[167]]
## [1] "ITS2-Bg014" "197_L001_R1_001.fastq"
##
## [[168]]
## [1] "ITS2-Bg015" "198_L001_R1_001.fastq"
##
## [[169]]
## [1] "ITS2-Bg016" "199_L001_R1_001.fastq"
##
## [[170]]
## [1] "ITS2-Bg017" "200_L001_R1_001.fastq"
##
## [[171]]
## [1] "ITS2-Bg018" "201_L001_R1_001.fastq"
##
## [[172]]
## [1] "ITS2-Bg019" "202_L001_R1_001.fastq"
##
## [[173]]
## [1] "ITS2-Bi001" "203_L001_R1_001.fastq"
##
## [[174]]
## [1] "ITS2-Bi002" "204_L001_R1_001.fastq"
##
## [[175]]
## [1] "ITS2-Bi003" "205_L001_R1_001.fastq"
##
## [[176]]
## [1] "ITS2-Bi004" "206_L001_R1_001.fastq"
##
## [[177]]
## [1] "ITS2-Bi005" "207_L001_R1_001.fastq"
##
## [[178]]
## [1] "ITS2-Bi006" "208_L001_R1_001.fastq"
##
## [[179]]
## [1] "ITS2-Bi007" "209_L001_R1_001.fastq"
##
## [[180]]
## [1] "ITS2-CKC0001" "210_L001_R1_001.fastq"
##
## [[181]]
## [1] "ITS2-ESE0004" "211_L001_R1_001.fastq"
##
## [[182]]
## [1] "ITS2-ext-neg-ctrl-20230909" "212_L001_R1_001.fastq"
##
## [[183]]
## [1] "ITS2-ext-neg-ctrl-20230923" "213_L001_R1_001.fastq"
##
## [[184]]
## [1] "ITS2-ext-neg-ctrl-20230924" "214_L001_R1_001.fastq"
##
## [[185]]
## [1] "ITS2-ext-neg-ctrl-20231007" "215_L001_R1_001.fastq"
##
## [[186]]
## [1] "ITS2-ext-neg-ctrl-20231008" "216_L001_R1_001.fastq"
##
## [[187]]
## [1] "ITS2-ext-neg-ctrl-20231009" "217_L001_R1_001.fastq"
##
## [[188]]
## [1] "ITS2-ext-neg-ctrl-2024220A" "218_L001_R1_001.fastq"
##
## [[189]]
## [1] "ITS2-ext-neg-ctrl-2024220B" "219_L001_R1_001.fastq"
##
## [[190]]
## [1] "ITS2-ext-neg-ctrl-2024221A" "220_L001_R1_001.fastq"
##
## [[191]]
## [1] "ITS2-ext-neg-ctrl-2024221B" "221_L001_R1_001.fastq"
##
## [[192]]
## [1] "ITS2-ext-neg-ctrl-2024222A" "222_L001_R1_001.fastq"
##
## [[193]]
## [1] "ITS2-ext-neg-ctrl-2024222B" "223_L001_R1_001.fastq"
##
## [[194]]
## [1] "ITS2-ext-neg-ctrl-2024312A" "224_L001_R1_001.fastq"
##
## [[195]]
## [1] "ITS2-ext-neg-ctrl-2024312B" "225_L001_R1_001.fastq"
##
## [[196]]
## [1] "ITS2-ext-neg-ctrl-2024314A" "226_L001_R1_001.fastq"
##
## [[197]]
## [1] "ITS2-ext-neg-ctrl-2024314B" "227_L001_R1_001.fastq"
##
## [[198]]
## [1] "ITS2-ext-neg-ctrl-2024319" "228_L001_R1_001.fastq"
##
## [[199]]
## [1] "ITS2-ext-neg-ctrl-2024320" "229_L001_R1_001.fastq"
##
## [[200]]
## [1] "ITS2-KLS0007" "230_L001_R1_001.fastq"
##
## [[201]]
## [1] "ITS2-KLS0027" "232_L001_R1_001.fastq"
##
## [[202]]
## [1] "ITS2-KLS0044" "233_L001_R1_001.fastq"
##
## [[203]]
## [1] "ITS2-KLS0045" "234_L001_R1_001.fastq"
##
## [[204]]
## [1] "ITS2-KLS0052" "235_L001_R1_001.fastq"
##
## [[205]]
## [1] "ITS2-KLS0054" "236_L001_R1_001.fastq"
##
## [[206]]
## [1] "ITS2-KLS0055" "237_L001_R1_001.fastq"
##
## [[207]]
## [1] "ITS2-KLS0071" "238_L001_R1_001.fastq"
##
## [[208]]
## [1] "ITS2-KLS0095" "239_L001_R1_001.fastq"
##
## [[209]]
## [1] "ITS2-KLS0096" "240_L001_R1_001.fastq"
##
## [[210]]
## [1] "ITS2-KLS0105" "241_L001_R1_001.fastq"
##
## [[211]]
## [1] "ITS2-KLS0106" "242_L001_R1_001.fastq"
##
## [[212]]
## [1] "ITS2-KLS0119" "243_L001_R1_001.fastq"
##
## [[213]]
## [1] "ITS2-KLS0134" "244_L001_R1_001.fastq"
##
## [[214]]
## [1] "ITS2-KLS0135" "245_L001_R1_001.fastq"
##
## [[215]]
## [1] "ITS2-KLS0136" "246_L001_R1_001.fastq"
##
## [[216]]
## [1] "ITS2-KLS0137" "247_L001_R1_001.fastq"
##
## [[217]]
## [1] "ITS2-KLS0138" "248_L001_R1_001.fastq"
##
## [[218]]
## [1] "ITS2-KLS0139" "249_L001_R1_001.fastq"
##
## [[219]]
## [1] "ITS2-KLS0150" "250_L001_R1_001.fastq"
##
## [[220]]
## [1] "ITS2-KLS0153" "251_L001_R1_001.fastq"
##
## [[221]]
## [1] "ITS2-KLS0155" "252_L001_R1_001.fastq"
##
## [[222]]
## [1] "ITS2-KLS0156" "253_L001_R1_001.fastq"
##
## [[223]]
## [1] "ITS2-KLS0159" "254_L001_R1_001.fastq"
##
## [[224]]
## [1] "ITS2-KLS0163" "255_L001_R1_001.fastq"
##
## [[225]]
## [1] "ITS2-KLS0165" "256_L001_R1_001.fastq"
##
## [[226]]
## [1] "ITS2-KLS0167" "257_L001_R1_001.fastq"
##
## [[227]]
## [1] "ITS2-KLS0168" "258_L001_R1_001.fastq"
##
## [[228]]
## [1] "ITS2-KLS0169" "259_L001_R1_001.fastq"
##
## [[229]]
## [1] "ITS2-KLS0170" "260_L001_R1_001.fastq"
##
## [[230]]
## [1] "ITS2-KLS0200" "261_L001_R1_001.fastq"
##
## [[231]]
## [1] "ITS2-KLS0201" "262_L001_R1_001.fastq"
##
## [[232]]
## [1] "ITS2-KLS0205" "263_L001_R1_001.fastq"
##
## [[233]]
## [1] "ITS2-KLS0209" "264_L001_R1_001.fastq"
##
## [[234]]
## [1] "ITS2-KLS0221" "265_L001_R1_001.fastq"
##
## [[235]]
## [1] "ITS2-KLS0224" "266_L001_R1_001.fastq"
##
## [[236]]
## [1] "ITS2-KLS0225" "267_L001_R1_001.fastq"
##
## [[237]]
## [1] "ITS2-KLS0227" "268_L001_R1_001.fastq"
##
## [[238]]
## [1] "ITS2-KLS0241" "269_L001_R1_001.fastq"
##
## [[239]]
## [1] "ITS2-KLS0244" "270_L001_R1_001.fastq"
##
## [[240]]
## [1] "ITS2-KLS0246" "271_L001_R1_001.fastq"
##
## [[241]]
## [1] "ITS2-KLS0248" "272_L001_R1_001.fastq"
##
## [[242]]
## [1] "ITS2-KLS0253" "273_L001_R1_001.fastq"
##
## [[243]]
## [1] "ITS2-KLS0254" "274_L001_R1_001.fastq"
##
## [[244]]
## [1] "ITS2-KLS0256" "231_L001_R1_001.fastq"
##
## [[245]]
## [1] "ITS2-KLS0259" "275_L001_R1_001.fastq"
##
## [[246]]
## [1] "ITS2-KLS0263" "276_L001_R1_001.fastq"
##
## [[247]]
## [1] "ITS2-KLS0266" "277_L001_R1_001.fastq"
##
## [[248]]
## [1] "ITS2-KLS0272" "278_L001_R1_001.fastq"
##
## [[249]]
## [1] "ITS2-pcr-its2-neg-ctrl-20231021-20231119"
## [2] "279_L001_R1_001.fastq"
##
## [[250]]
## [1] "ITS2-pcr-its2-neg-ctrl-20231022-20231120"
## [2] "280_L001_R1_001.fastq"
##
## [[251]]
## [1] "ITS2-pcr-its2-neg-ctrl-20231023" "281_L001_R1_001.fastq"
##
## [[252]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240411" "282_L001_R1_001.fastq"
##
## [[253]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240416" "283_L001_R1_001.fastq"
##
## [[254]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240417" "284_L001_R1_001.fastq"
##
## [[255]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240418A" "285_L001_R1_001.fastq"
##
## [[256]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240418B" "286_L001_R1_001.fastq"
##
## [[257]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240517" "287_L001_R1_001.fastq"
##
## [[258]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240524" "288_L001_R1_001.fastq"
##
## [[259]]
## [1] "ITS2-pcr-its2-neg-ctrl-Saskia-20240411"
## [2] "289_L001_R1_001.fastq"
##
## [[260]]
## [1] "ITS2-SCA0009" "290_L001_R1_001.fastq"
##
## [[261]]
## [1] "ITS2-SCA0010" "291_L001_R1_001.fastq"
##
## [[262]]
## [1] "ITS2-SCA0013" "292_L001_R1_001.fastq" lapply(strsplit(rownames(as.data.frame(out)), "_S"), function(l) l[[1]])## [[1]]
## [1] "ITS2-2020-6-16-H1"
##
## [[2]]
## [1] "ITS2-2020-6-16-H5"
##
## [[3]]
## [1] "ITS2-2020-6-16-H6"
##
## [[4]]
## [1] "ITS2-2020-6-17-H2"
##
## [[5]]
## [1] "ITS2-2020-6-17-H4"
##
## [[6]]
## [1] "ITS2-2020-6-17-H8"
##
## [[7]]
## [1] "ITS2-2020-6-18-H3"
##
## [[8]]
## [1] "ITS2-2020-6-18-H7"
##
## [[9]]
## [1] "ITS2-2020-6-18-H9"
##
## [[10]]
## [1] "ITS2-2020-6-3-H1"
##
## [[11]]
## [1] "ITS2-2020-6-3-H5"
##
## [[12]]
## [1] "ITS2-2020-6-3-H6"
##
## [[13]]
## [1] "ITS2-2020-6-30-H1"
##
## [[14]]
## [1] "ITS2-2020-6-30-H5"
##
## [[15]]
## [1] "ITS2-2020-6-30-H6"
##
## [[16]]
## [1] "ITS2-2020-6-4-H2"
##
## [[17]]
## [1] "ITS2-2020-6-4-H4"
##
## [[18]]
## [1] "ITS2-2020-6-4-H8"
##
## [[19]]
## [1] "ITS2-2020-6-5-H3"
##
## [[20]]
## [1] "ITS2-2020-6-5-H7"
##
## [[21]]
## [1] "ITS2-2020-6-5-H9"
##
## [[22]]
## [1] "ITS2-2020-7-1-H2"
##
## [[23]]
## [1] "ITS2-2020-7-1-H4"
##
## [[24]]
## [1] "ITS2-2020-7-1-H8"
##
## [[25]]
## [1] "ITS2-2020-7-14-H1"
##
## [[26]]
## [1] "ITS2-2020-7-14-H5"
##
## [[27]]
## [1] "ITS2-2020-7-14-H6"
##
## [[28]]
## [1] "ITS2-2020-7-15-H2"
##
## [[29]]
## [1] "ITS2-2020-7-15-H4"
##
## [[30]]
## [1] "ITS2-2020-7-15-H8"
##
## [[31]]
## [1] "ITS2-2020-7-16-H3"
##
## [[32]]
## [1] "ITS2-2020-7-16-H7"
##
## [[33]]
## [1] "ITS2-2020-7-16-H9"
##
## [[34]]
## [1] "ITS2-2020-7-2-H3"
##
## [[35]]
## [1] "ITS2-2020-7-2-H7"
##
## [[36]]
## [1] "ITS2-2020-7-2-H9"
##
## [[37]]
## [1] "ITS2-2021-6-13-H1"
##
## [[38]]
## [1] "ITS2-2021-6-13-H3"
##
## [[39]]
## [1] "ITS2-2021-6-14-H11"
##
## [[40]]
## [1] "ITS2-2021-6-14-H6"
##
## [[41]]
## [1] "ITS2-2021-6-14-H7"
##
## [[42]]
## [1] "ITS2-2021-6-15-H8"
##
## [[43]]
## [1] "ITS2-2021-6-21-H10"
##
## [[44]]
## [1] "ITS2-2021-6-21-H12"
##
## [[45]]
## [1] "ITS2-2021-6-21-H9"
##
## [[46]]
## [1] "ITS2-2021-6-27-H21"
##
## [[47]]
## [1] "ITS2-2021-6-27-H22"
##
## [[48]]
## [1] "ITS2-2021-6-27-H27"
##
## [[49]]
## [1] "ITS2-2021-6-28-H25"
##
## [[50]]
## [1] "ITS2-2021-6-28-H26"
##
## [[51]]
## [1] "ITS2-2021-6-28-H28"
##
## [[52]]
## [1] "ITS2-2021-6-29-H17"
##
## [[53]]
## [1] "ITS2-2021-6-29-H23"
##
## [[54]]
## [1] "ITS2-2021-6-29-H24"
##
## [[55]]
## [1] "ITS2-2021-6-4-H21"
##
## [[56]]
## [1] "ITS2-2021-6-4-H22"
##
## [[57]]
## [1] "ITS2-2021-6-4-H27"
##
## [[58]]
## [1] "ITS2-2021-6-5-H18"
##
## [[59]]
## [1] "ITS2-2021-6-5-H25"
##
## [[60]]
## [1] "ITS2-2021-6-5-H26"
##
## [[61]]
## [1] "ITS2-2021-6-6-H17"
##
## [[62]]
## [1] "ITS2-2021-6-6-H24"
##
## [[63]]
## [1] "ITS2-2021-6-7-H23"
##
## [[64]]
## [1] "ITS2-2021-7-14-H10"
##
## [[65]]
## [1] "ITS2-2021-7-14-H12"
##
## [[66]]
## [1] "ITS2-2021-7-20-H27"
##
## [[67]]
## [1] "ITS2-2021-7-21-H25"
##
## [[68]]
## [1] "ITS2-2021-7-21-H26"
##
## [[69]]
## [1] "ITS2-2021-7-21-H28"
##
## [[70]]
## [1] "ITS2-2021-7-6-H11"
##
## [[71]]
## [1] "ITS2-2021-7-6-H30"
##
## [[72]]
## [1] "ITS2-2021-7-6-H6"
##
## [[73]]
## [1] "ITS2-2021-7-7-H4"
##
## [[74]]
## [1] "ITS2-2021-7-7-H8"
##
## [[75]]
## [1] "ITS2-2021-7-8-H3"
##
## [[76]]
## [1] "ITS2-2023-6-12-H3"
##
## [[77]]
## [1] "ITS2-2023-6-12-H5"
##
## [[78]]
## [1] "ITS2-2023-6-12-H7"
##
## [[79]]
## [1] "ITS2-2023-6-13-H6"
##
## [[80]]
## [1] "ITS2-2023-6-13-H8"
##
## [[81]]
## [1] "ITS2-2023-6-13-H9"
##
## [[82]]
## [1] "ITS2-2023-6-14-H3"
##
## [[83]]
## [1] "ITS2-2023-6-14-H7"
##
## [[84]]
## [1] "ITS2-2023-6-14-H9"
##
## [[85]]
## [1] "ITS2-2023-6-16-H5"
##
## [[86]]
## [1] "ITS2-2023-6-24-H6"
##
## [[87]]
## [1] "ITS2-2023-6-24-H8"
##
## [[88]]
## [1] "ITS2-2023-6-25-H2"
##
## [[89]]
## [1] "ITS2-2023-6-25-H4"
##
## [[90]]
## [1] "ITS2-2023-6-26-H1"
##
## [[91]]
## [1] "ITS2-2023-6-26-H7"
##
## [[92]]
## [1] "ITS2-2023-6-27-H3"
##
## [[93]]
## [1] "ITS2-2023-6-27-H5"
##
## [[94]]
## [1] "ITS2-2023-6-8-H1"
##
## [[95]]
## [1] "ITS2-2023-6-8-H2"
##
## [[96]]
## [1] "ITS2-2023-6-8-H4"
##
## [[97]]
## [1] "ITS2-2023-6-9-H2"
##
## [[98]]
## [1] "ITS2-2023-6-9-H4"
##
## [[99]]
## [1] "ITS2-2023-7-15-H6"
##
## [[100]]
## [1] "ITS2-2023-7-16-H4"
##
## [[101]]
## [1] "ITS2-2023-7-17-H1"
##
## [[102]]
## [1] "ITS2-2023-7-18-H3"
##
## [[103]]
## [1] "ITS2-2023-7-18-H7"
##
## [[104]]
## [1] "ITS2-2023-7-29-H5"
##
## [[105]]
## [1] "ITS2-2023-7-29-H7"
##
## [[106]]
## [1] "ITS2-2023-7-30-H8"
##
## [[107]]
## [1] "ITS2-2023-7-30-H9"
##
## [[108]]
## [1] "ITS2-2023-7-5-H1"
##
## [[109]]
## [1] "ITS2-2023-7-5-H2"
##
## [[110]]
## [1] "ITS2-2023-7-5-H4"
##
## [[111]]
## [1] "ITS2-2023-7-6-H6"
##
## [[112]]
## [1] "ITS2-2023-7-6-H8"
##
## [[113]]
## [1] "ITS2-2023-7-6-H9"
##
## [[114]]
## [1] "ITS2-2023-7-8-H3"
##
## [[115]]
## [1] "ITS2-2023-7-8-H5"
##
## [[116]]
## [1] "ITS2-2023-7-8-H7"
##
## [[117]]
## [1] "ITS2-2023-8-4-H2"
##
## [[118]]
## [1] "ITS2-2023-8-4-H5"
##
## [[119]]
## [1] "ITS2-2023-8-4-H6"
##
## [[120]]
## [1] "ITS2-2023-8-4-H7"
##
## [[121]]
## [1] "ITS2-2023-8-4-H8"
##
## [[122]]
## [1] "ITS2-2023-8-4-H9"
##
## [[123]]
## [1] "ITS2-Ba001"
##
## [[124]]
## [1] "ITS2-Ba002"
##
## [[125]]
## [1] "ITS2-Ba003"
##
## [[126]]
## [1] "ITS2-Bb001"
##
## [[127]]
## [1] "ITS2-Bb002"
##
## [[128]]
## [1] "ITS2-Bb003"
##
## [[129]]
## [1] "ITS2-Bb004"
##
## [[130]]
## [1] "ITS2-Bb005"
##
## [[131]]
## [1] "ITS2-Bb007"
##
## [[132]]
## [1] "ITS2-Bb008"
##
## [[133]]
## [1] "ITS2-Bb009"
##
## [[134]]
## [1] "ITS2-Bb010"
##
## [[135]]
## [1] "ITS2-Bb011"
##
## [[136]]
## [1] "ITS2-Bb012"
##
## [[137]]
## [1] "ITS2-Bb013"
##
## [[138]]
## [1] "ITS2-Bb014"
##
## [[139]]
## [1] "ITS2-Bb015"
##
## [[140]]
## [1] "ITS2-Bb016"
##
## [[141]]
## [1] "ITS2-Bb017"
##
## [[142]]
## [1] "ITS2-Bb018"
##
## [[143]]
## [1] "ITS2-Bb019"
##
## [[144]]
## [1] "ITS2-Bb020"
##
## [[145]]
## [1] "ITS2-Bb021"
##
## [[146]]
## [1] "ITS2-Bb022"
##
## [[147]]
## [1] "ITS2-Bb023"
##
## [[148]]
## [1] "ITS2-Bb024"
##
## [[149]]
## [1] "ITS2-Bb025"
##
## [[150]]
## [1] "ITS2-Bf001"
##
## [[151]]
## [1] "ITS2-Bf002"
##
## [[152]]
## [1] "ITS2-Bf003"
##
## [[153]]
## [1] "ITS2-Bf004"
##
## [[154]]
## [1] "ITS2-Bg001"
##
## [[155]]
## [1] "ITS2-Bg002"
##
## [[156]]
## [1] "ITS2-Bg003"
##
## [[157]]
## [1] "ITS2-Bg004"
##
## [[158]]
## [1] "ITS2-Bg005"
##
## [[159]]
## [1] "ITS2-Bg006"
##
## [[160]]
## [1] "ITS2-Bg007"
##
## [[161]]
## [1] "ITS2-Bg008"
##
## [[162]]
## [1] "ITS2-Bg009"
##
## [[163]]
## [1] "ITS2-Bg010"
##
## [[164]]
## [1] "ITS2-Bg011"
##
## [[165]]
## [1] "ITS2-Bg012"
##
## [[166]]
## [1] "ITS2-Bg013"
##
## [[167]]
## [1] "ITS2-Bg014"
##
## [[168]]
## [1] "ITS2-Bg015"
##
## [[169]]
## [1] "ITS2-Bg016"
##
## [[170]]
## [1] "ITS2-Bg017"
##
## [[171]]
## [1] "ITS2-Bg018"
##
## [[172]]
## [1] "ITS2-Bg019"
##
## [[173]]
## [1] "ITS2-Bi001"
##
## [[174]]
## [1] "ITS2-Bi002"
##
## [[175]]
## [1] "ITS2-Bi003"
##
## [[176]]
## [1] "ITS2-Bi004"
##
## [[177]]
## [1] "ITS2-Bi005"
##
## [[178]]
## [1] "ITS2-Bi006"
##
## [[179]]
## [1] "ITS2-Bi007"
##
## [[180]]
## [1] "ITS2-CKC0001"
##
## [[181]]
## [1] "ITS2-ESE0004"
##
## [[182]]
## [1] "ITS2-ext-neg-ctrl-20230909"
##
## [[183]]
## [1] "ITS2-ext-neg-ctrl-20230923"
##
## [[184]]
## [1] "ITS2-ext-neg-ctrl-20230924"
##
## [[185]]
## [1] "ITS2-ext-neg-ctrl-20231007"
##
## [[186]]
## [1] "ITS2-ext-neg-ctrl-20231008"
##
## [[187]]
## [1] "ITS2-ext-neg-ctrl-20231009"
##
## [[188]]
## [1] "ITS2-ext-neg-ctrl-2024220A"
##
## [[189]]
## [1] "ITS2-ext-neg-ctrl-2024220B"
##
## [[190]]
## [1] "ITS2-ext-neg-ctrl-2024221A"
##
## [[191]]
## [1] "ITS2-ext-neg-ctrl-2024221B"
##
## [[192]]
## [1] "ITS2-ext-neg-ctrl-2024222A"
##
## [[193]]
## [1] "ITS2-ext-neg-ctrl-2024222B"
##
## [[194]]
## [1] "ITS2-ext-neg-ctrl-2024312A"
##
## [[195]]
## [1] "ITS2-ext-neg-ctrl-2024312B"
##
## [[196]]
## [1] "ITS2-ext-neg-ctrl-2024314A"
##
## [[197]]
## [1] "ITS2-ext-neg-ctrl-2024314B"
##
## [[198]]
## [1] "ITS2-ext-neg-ctrl-2024319"
##
## [[199]]
## [1] "ITS2-ext-neg-ctrl-2024320"
##
## [[200]]
## [1] "ITS2-KLS0007"
##
## [[201]]
## [1] "ITS2-KLS0027"
##
## [[202]]
## [1] "ITS2-KLS0044"
##
## [[203]]
## [1] "ITS2-KLS0045"
##
## [[204]]
## [1] "ITS2-KLS0052"
##
## [[205]]
## [1] "ITS2-KLS0054"
##
## [[206]]
## [1] "ITS2-KLS0055"
##
## [[207]]
## [1] "ITS2-KLS0071"
##
## [[208]]
## [1] "ITS2-KLS0095"
##
## [[209]]
## [1] "ITS2-KLS0096"
##
## [[210]]
## [1] "ITS2-KLS0105"
##
## [[211]]
## [1] "ITS2-KLS0106"
##
## [[212]]
## [1] "ITS2-KLS0119"
##
## [[213]]
## [1] "ITS2-KLS0134"
##
## [[214]]
## [1] "ITS2-KLS0135"
##
## [[215]]
## [1] "ITS2-KLS0136"
##
## [[216]]
## [1] "ITS2-KLS0137"
##
## [[217]]
## [1] "ITS2-KLS0138"
##
## [[218]]
## [1] "ITS2-KLS0139"
##
## [[219]]
## [1] "ITS2-KLS0150"
##
## [[220]]
## [1] "ITS2-KLS0153"
##
## [[221]]
## [1] "ITS2-KLS0155"
##
## [[222]]
## [1] "ITS2-KLS0156"
##
## [[223]]
## [1] "ITS2-KLS0159"
##
## [[224]]
## [1] "ITS2-KLS0163"
##
## [[225]]
## [1] "ITS2-KLS0165"
##
## [[226]]
## [1] "ITS2-KLS0167"
##
## [[227]]
## [1] "ITS2-KLS0168"
##
## [[228]]
## [1] "ITS2-KLS0169"
##
## [[229]]
## [1] "ITS2-KLS0170"
##
## [[230]]
## [1] "ITS2-KLS0200"
##
## [[231]]
## [1] "ITS2-KLS0201"
##
## [[232]]
## [1] "ITS2-KLS0205"
##
## [[233]]
## [1] "ITS2-KLS0209"
##
## [[234]]
## [1] "ITS2-KLS0221"
##
## [[235]]
## [1] "ITS2-KLS0224"
##
## [[236]]
## [1] "ITS2-KLS0225"
##
## [[237]]
## [1] "ITS2-KLS0227"
##
## [[238]]
## [1] "ITS2-KLS0241"
##
## [[239]]
## [1] "ITS2-KLS0244"
##
## [[240]]
## [1] "ITS2-KLS0246"
##
## [[241]]
## [1] "ITS2-KLS0248"
##
## [[242]]
## [1] "ITS2-KLS0253"
##
## [[243]]
## [1] "ITS2-KLS0254"
##
## [[244]]
## [1] "ITS2-KLS0256"
##
## [[245]]
## [1] "ITS2-KLS0259"
##
## [[246]]
## [1] "ITS2-KLS0263"
##
## [[247]]
## [1] "ITS2-KLS0266"
##
## [[248]]
## [1] "ITS2-KLS0272"
##
## [[249]]
## [1] "ITS2-pcr-its2-neg-ctrl-20231021-20231119"
##
## [[250]]
## [1] "ITS2-pcr-its2-neg-ctrl-20231022-20231120"
##
## [[251]]
## [1] "ITS2-pcr-its2-neg-ctrl-20231023"
##
## [[252]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240411"
##
## [[253]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240416"
##
## [[254]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240417"
##
## [[255]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240418A"
##
## [[256]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240418B"
##
## [[257]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240517"
##
## [[258]]
## [1] "ITS2-pcr-its2-neg-ctrl-20240524"
##
## [[259]]
## [1] "ITS2-pcr-its2-neg-ctrl-Saskia-20240411"
##
## [[260]]
## [1] "ITS2-SCA0009"
##
## [[261]]
## [1] "ITS2-SCA0010"
##
## [[262]]
## [1] "ITS2-SCA0013" strsplit(sapply(strsplit(rownames(as.data.frame(out)), "_S"), function(l) l[[1]]),"-")## [[1]]
## [1] "ITS2" "2020" "6" "16" "H1"
##
## [[2]]
## [1] "ITS2" "2020" "6" "16" "H5"
##
## [[3]]
## [1] "ITS2" "2020" "6" "16" "H6"
##
## [[4]]
## [1] "ITS2" "2020" "6" "17" "H2"
##
## [[5]]
## [1] "ITS2" "2020" "6" "17" "H4"
##
## [[6]]
## [1] "ITS2" "2020" "6" "17" "H8"
##
## [[7]]
## [1] "ITS2" "2020" "6" "18" "H3"
##
## [[8]]
## [1] "ITS2" "2020" "6" "18" "H7"
##
## [[9]]
## [1] "ITS2" "2020" "6" "18" "H9"
##
## [[10]]
## [1] "ITS2" "2020" "6" "3" "H1"
##
## [[11]]
## [1] "ITS2" "2020" "6" "3" "H5"
##
## [[12]]
## [1] "ITS2" "2020" "6" "3" "H6"
##
## [[13]]
## [1] "ITS2" "2020" "6" "30" "H1"
##
## [[14]]
## [1] "ITS2" "2020" "6" "30" "H5"
##
## [[15]]
## [1] "ITS2" "2020" "6" "30" "H6"
##
## [[16]]
## [1] "ITS2" "2020" "6" "4" "H2"
##
## [[17]]
## [1] "ITS2" "2020" "6" "4" "H4"
##
## [[18]]
## [1] "ITS2" "2020" "6" "4" "H8"
##
## [[19]]
## [1] "ITS2" "2020" "6" "5" "H3"
##
## [[20]]
## [1] "ITS2" "2020" "6" "5" "H7"
##
## [[21]]
## [1] "ITS2" "2020" "6" "5" "H9"
##
## [[22]]
## [1] "ITS2" "2020" "7" "1" "H2"
##
## [[23]]
## [1] "ITS2" "2020" "7" "1" "H4"
##
## [[24]]
## [1] "ITS2" "2020" "7" "1" "H8"
##
## [[25]]
## [1] "ITS2" "2020" "7" "14" "H1"
##
## [[26]]
## [1] "ITS2" "2020" "7" "14" "H5"
##
## [[27]]
## [1] "ITS2" "2020" "7" "14" "H6"
##
## [[28]]
## [1] "ITS2" "2020" "7" "15" "H2"
##
## [[29]]
## [1] "ITS2" "2020" "7" "15" "H4"
##
## [[30]]
## [1] "ITS2" "2020" "7" "15" "H8"
##
## [[31]]
## [1] "ITS2" "2020" "7" "16" "H3"
##
## [[32]]
## [1] "ITS2" "2020" "7" "16" "H7"
##
## [[33]]
## [1] "ITS2" "2020" "7" "16" "H9"
##
## [[34]]
## [1] "ITS2" "2020" "7" "2" "H3"
##
## [[35]]
## [1] "ITS2" "2020" "7" "2" "H7"
##
## [[36]]
## [1] "ITS2" "2020" "7" "2" "H9"
##
## [[37]]
## [1] "ITS2" "2021" "6" "13" "H1"
##
## [[38]]
## [1] "ITS2" "2021" "6" "13" "H3"
##
## [[39]]
## [1] "ITS2" "2021" "6" "14" "H11"
##
## [[40]]
## [1] "ITS2" "2021" "6" "14" "H6"
##
## [[41]]
## [1] "ITS2" "2021" "6" "14" "H7"
##
## [[42]]
## [1] "ITS2" "2021" "6" "15" "H8"
##
## [[43]]
## [1] "ITS2" "2021" "6" "21" "H10"
##
## [[44]]
## [1] "ITS2" "2021" "6" "21" "H12"
##
## [[45]]
## [1] "ITS2" "2021" "6" "21" "H9"
##
## [[46]]
## [1] "ITS2" "2021" "6" "27" "H21"
##
## [[47]]
## [1] "ITS2" "2021" "6" "27" "H22"
##
## [[48]]
## [1] "ITS2" "2021" "6" "27" "H27"
##
## [[49]]
## [1] "ITS2" "2021" "6" "28" "H25"
##
## [[50]]
## [1] "ITS2" "2021" "6" "28" "H26"
##
## [[51]]
## [1] "ITS2" "2021" "6" "28" "H28"
##
## [[52]]
## [1] "ITS2" "2021" "6" "29" "H17"
##
## [[53]]
## [1] "ITS2" "2021" "6" "29" "H23"
##
## [[54]]
## [1] "ITS2" "2021" "6" "29" "H24"
##
## [[55]]
## [1] "ITS2" "2021" "6" "4" "H21"
##
## [[56]]
## [1] "ITS2" "2021" "6" "4" "H22"
##
## [[57]]
## [1] "ITS2" "2021" "6" "4" "H27"
##
## [[58]]
## [1] "ITS2" "2021" "6" "5" "H18"
##
## [[59]]
## [1] "ITS2" "2021" "6" "5" "H25"
##
## [[60]]
## [1] "ITS2" "2021" "6" "5" "H26"
##
## [[61]]
## [1] "ITS2" "2021" "6" "6" "H17"
##
## [[62]]
## [1] "ITS2" "2021" "6" "6" "H24"
##
## [[63]]
## [1] "ITS2" "2021" "6" "7" "H23"
##
## [[64]]
## [1] "ITS2" "2021" "7" "14" "H10"
##
## [[65]]
## [1] "ITS2" "2021" "7" "14" "H12"
##
## [[66]]
## [1] "ITS2" "2021" "7" "20" "H27"
##
## [[67]]
## [1] "ITS2" "2021" "7" "21" "H25"
##
## [[68]]
## [1] "ITS2" "2021" "7" "21" "H26"
##
## [[69]]
## [1] "ITS2" "2021" "7" "21" "H28"
##
## [[70]]
## [1] "ITS2" "2021" "7" "6" "H11"
##
## [[71]]
## [1] "ITS2" "2021" "7" "6" "H30"
##
## [[72]]
## [1] "ITS2" "2021" "7" "6" "H6"
##
## [[73]]
## [1] "ITS2" "2021" "7" "7" "H4"
##
## [[74]]
## [1] "ITS2" "2021" "7" "7" "H8"
##
## [[75]]
## [1] "ITS2" "2021" "7" "8" "H3"
##
## [[76]]
## [1] "ITS2" "2023" "6" "12" "H3"
##
## [[77]]
## [1] "ITS2" "2023" "6" "12" "H5"
##
## [[78]]
## [1] "ITS2" "2023" "6" "12" "H7"
##
## [[79]]
## [1] "ITS2" "2023" "6" "13" "H6"
##
## [[80]]
## [1] "ITS2" "2023" "6" "13" "H8"
##
## [[81]]
## [1] "ITS2" "2023" "6" "13" "H9"
##
## [[82]]
## [1] "ITS2" "2023" "6" "14" "H3"
##
## [[83]]
## [1] "ITS2" "2023" "6" "14" "H7"
##
## [[84]]
## [1] "ITS2" "2023" "6" "14" "H9"
##
## [[85]]
## [1] "ITS2" "2023" "6" "16" "H5"
##
## [[86]]
## [1] "ITS2" "2023" "6" "24" "H6"
##
## [[87]]
## [1] "ITS2" "2023" "6" "24" "H8"
##
## [[88]]
## [1] "ITS2" "2023" "6" "25" "H2"
##
## [[89]]
## [1] "ITS2" "2023" "6" "25" "H4"
##
## [[90]]
## [1] "ITS2" "2023" "6" "26" "H1"
##
## [[91]]
## [1] "ITS2" "2023" "6" "26" "H7"
##
## [[92]]
## [1] "ITS2" "2023" "6" "27" "H3"
##
## [[93]]
## [1] "ITS2" "2023" "6" "27" "H5"
##
## [[94]]
## [1] "ITS2" "2023" "6" "8" "H1"
##
## [[95]]
## [1] "ITS2" "2023" "6" "8" "H2"
##
## [[96]]
## [1] "ITS2" "2023" "6" "8" "H4"
##
## [[97]]
## [1] "ITS2" "2023" "6" "9" "H2"
##
## [[98]]
## [1] "ITS2" "2023" "6" "9" "H4"
##
## [[99]]
## [1] "ITS2" "2023" "7" "15" "H6"
##
## [[100]]
## [1] "ITS2" "2023" "7" "16" "H4"
##
## [[101]]
## [1] "ITS2" "2023" "7" "17" "H1"
##
## [[102]]
## [1] "ITS2" "2023" "7" "18" "H3"
##
## [[103]]
## [1] "ITS2" "2023" "7" "18" "H7"
##
## [[104]]
## [1] "ITS2" "2023" "7" "29" "H5"
##
## [[105]]
## [1] "ITS2" "2023" "7" "29" "H7"
##
## [[106]]
## [1] "ITS2" "2023" "7" "30" "H8"
##
## [[107]]
## [1] "ITS2" "2023" "7" "30" "H9"
##
## [[108]]
## [1] "ITS2" "2023" "7" "5" "H1"
##
## [[109]]
## [1] "ITS2" "2023" "7" "5" "H2"
##
## [[110]]
## [1] "ITS2" "2023" "7" "5" "H4"
##
## [[111]]
## [1] "ITS2" "2023" "7" "6" "H6"
##
## [[112]]
## [1] "ITS2" "2023" "7" "6" "H8"
##
## [[113]]
## [1] "ITS2" "2023" "7" "6" "H9"
##
## [[114]]
## [1] "ITS2" "2023" "7" "8" "H3"
##
## [[115]]
## [1] "ITS2" "2023" "7" "8" "H5"
##
## [[116]]
## [1] "ITS2" "2023" "7" "8" "H7"
##
## [[117]]
## [1] "ITS2" "2023" "8" "4" "H2"
##
## [[118]]
## [1] "ITS2" "2023" "8" "4" "H5"
##
## [[119]]
## [1] "ITS2" "2023" "8" "4" "H6"
##
## [[120]]
## [1] "ITS2" "2023" "8" "4" "H7"
##
## [[121]]
## [1] "ITS2" "2023" "8" "4" "H8"
##
## [[122]]
## [1] "ITS2" "2023" "8" "4" "H9"
##
## [[123]]
## [1] "ITS2" "Ba001"
##
## [[124]]
## [1] "ITS2" "Ba002"
##
## [[125]]
## [1] "ITS2" "Ba003"
##
## [[126]]
## [1] "ITS2" "Bb001"
##
## [[127]]
## [1] "ITS2" "Bb002"
##
## [[128]]
## [1] "ITS2" "Bb003"
##
## [[129]]
## [1] "ITS2" "Bb004"
##
## [[130]]
## [1] "ITS2" "Bb005"
##
## [[131]]
## [1] "ITS2" "Bb007"
##
## [[132]]
## [1] "ITS2" "Bb008"
##
## [[133]]
## [1] "ITS2" "Bb009"
##
## [[134]]
## [1] "ITS2" "Bb010"
##
## [[135]]
## [1] "ITS2" "Bb011"
##
## [[136]]
## [1] "ITS2" "Bb012"
##
## [[137]]
## [1] "ITS2" "Bb013"
##
## [[138]]
## [1] "ITS2" "Bb014"
##
## [[139]]
## [1] "ITS2" "Bb015"
##
## [[140]]
## [1] "ITS2" "Bb016"
##
## [[141]]
## [1] "ITS2" "Bb017"
##
## [[142]]
## [1] "ITS2" "Bb018"
##
## [[143]]
## [1] "ITS2" "Bb019"
##
## [[144]]
## [1] "ITS2" "Bb020"
##
## [[145]]
## [1] "ITS2" "Bb021"
##
## [[146]]
## [1] "ITS2" "Bb022"
##
## [[147]]
## [1] "ITS2" "Bb023"
##
## [[148]]
## [1] "ITS2" "Bb024"
##
## [[149]]
## [1] "ITS2" "Bb025"
##
## [[150]]
## [1] "ITS2" "Bf001"
##
## [[151]]
## [1] "ITS2" "Bf002"
##
## [[152]]
## [1] "ITS2" "Bf003"
##
## [[153]]
## [1] "ITS2" "Bf004"
##
## [[154]]
## [1] "ITS2" "Bg001"
##
## [[155]]
## [1] "ITS2" "Bg002"
##
## [[156]]
## [1] "ITS2" "Bg003"
##
## [[157]]
## [1] "ITS2" "Bg004"
##
## [[158]]
## [1] "ITS2" "Bg005"
##
## [[159]]
## [1] "ITS2" "Bg006"
##
## [[160]]
## [1] "ITS2" "Bg007"
##
## [[161]]
## [1] "ITS2" "Bg008"
##
## [[162]]
## [1] "ITS2" "Bg009"
##
## [[163]]
## [1] "ITS2" "Bg010"
##
## [[164]]
## [1] "ITS2" "Bg011"
##
## [[165]]
## [1] "ITS2" "Bg012"
##
## [[166]]
## [1] "ITS2" "Bg013"
##
## [[167]]
## [1] "ITS2" "Bg014"
##
## [[168]]
## [1] "ITS2" "Bg015"
##
## [[169]]
## [1] "ITS2" "Bg016"
##
## [[170]]
## [1] "ITS2" "Bg017"
##
## [[171]]
## [1] "ITS2" "Bg018"
##
## [[172]]
## [1] "ITS2" "Bg019"
##
## [[173]]
## [1] "ITS2" "Bi001"
##
## [[174]]
## [1] "ITS2" "Bi002"
##
## [[175]]
## [1] "ITS2" "Bi003"
##
## [[176]]
## [1] "ITS2" "Bi004"
##
## [[177]]
## [1] "ITS2" "Bi005"
##
## [[178]]
## [1] "ITS2" "Bi006"
##
## [[179]]
## [1] "ITS2" "Bi007"
##
## [[180]]
## [1] "ITS2" "CKC0001"
##
## [[181]]
## [1] "ITS2" "ESE0004"
##
## [[182]]
## [1] "ITS2" "ext" "neg" "ctrl" "20230909"
##
## [[183]]
## [1] "ITS2" "ext" "neg" "ctrl" "20230923"
##
## [[184]]
## [1] "ITS2" "ext" "neg" "ctrl" "20230924"
##
## [[185]]
## [1] "ITS2" "ext" "neg" "ctrl" "20231007"
##
## [[186]]
## [1] "ITS2" "ext" "neg" "ctrl" "20231008"
##
## [[187]]
## [1] "ITS2" "ext" "neg" "ctrl" "20231009"
##
## [[188]]
## [1] "ITS2" "ext" "neg" "ctrl" "2024220A"
##
## [[189]]
## [1] "ITS2" "ext" "neg" "ctrl" "2024220B"
##
## [[190]]
## [1] "ITS2" "ext" "neg" "ctrl" "2024221A"
##
## [[191]]
## [1] "ITS2" "ext" "neg" "ctrl" "2024221B"
##
## [[192]]
## [1] "ITS2" "ext" "neg" "ctrl" "2024222A"
##
## [[193]]
## [1] "ITS2" "ext" "neg" "ctrl" "2024222B"
##
## [[194]]
## [1] "ITS2" "ext" "neg" "ctrl" "2024312A"
##
## [[195]]
## [1] "ITS2" "ext" "neg" "ctrl" "2024312B"
##
## [[196]]
## [1] "ITS2" "ext" "neg" "ctrl" "2024314A"
##
## [[197]]
## [1] "ITS2" "ext" "neg" "ctrl" "2024314B"
##
## [[198]]
## [1] "ITS2" "ext" "neg" "ctrl" "2024319"
##
## [[199]]
## [1] "ITS2" "ext" "neg" "ctrl" "2024320"
##
## [[200]]
## [1] "ITS2" "KLS0007"
##
## [[201]]
## [1] "ITS2" "KLS0027"
##
## [[202]]
## [1] "ITS2" "KLS0044"
##
## [[203]]
## [1] "ITS2" "KLS0045"
##
## [[204]]
## [1] "ITS2" "KLS0052"
##
## [[205]]
## [1] "ITS2" "KLS0054"
##
## [[206]]
## [1] "ITS2" "KLS0055"
##
## [[207]]
## [1] "ITS2" "KLS0071"
##
## [[208]]
## [1] "ITS2" "KLS0095"
##
## [[209]]
## [1] "ITS2" "KLS0096"
##
## [[210]]
## [1] "ITS2" "KLS0105"
##
## [[211]]
## [1] "ITS2" "KLS0106"
##
## [[212]]
## [1] "ITS2" "KLS0119"
##
## [[213]]
## [1] "ITS2" "KLS0134"
##
## [[214]]
## [1] "ITS2" "KLS0135"
##
## [[215]]
## [1] "ITS2" "KLS0136"
##
## [[216]]
## [1] "ITS2" "KLS0137"
##
## [[217]]
## [1] "ITS2" "KLS0138"
##
## [[218]]
## [1] "ITS2" "KLS0139"
##
## [[219]]
## [1] "ITS2" "KLS0150"
##
## [[220]]
## [1] "ITS2" "KLS0153"
##
## [[221]]
## [1] "ITS2" "KLS0155"
##
## [[222]]
## [1] "ITS2" "KLS0156"
##
## [[223]]
## [1] "ITS2" "KLS0159"
##
## [[224]]
## [1] "ITS2" "KLS0163"
##
## [[225]]
## [1] "ITS2" "KLS0165"
##
## [[226]]
## [1] "ITS2" "KLS0167"
##
## [[227]]
## [1] "ITS2" "KLS0168"
##
## [[228]]
## [1] "ITS2" "KLS0169"
##
## [[229]]
## [1] "ITS2" "KLS0170"
##
## [[230]]
## [1] "ITS2" "KLS0200"
##
## [[231]]
## [1] "ITS2" "KLS0201"
##
## [[232]]
## [1] "ITS2" "KLS0205"
##
## [[233]]
## [1] "ITS2" "KLS0209"
##
## [[234]]
## [1] "ITS2" "KLS0221"
##
## [[235]]
## [1] "ITS2" "KLS0224"
##
## [[236]]
## [1] "ITS2" "KLS0225"
##
## [[237]]
## [1] "ITS2" "KLS0227"
##
## [[238]]
## [1] "ITS2" "KLS0241"
##
## [[239]]
## [1] "ITS2" "KLS0244"
##
## [[240]]
## [1] "ITS2" "KLS0246"
##
## [[241]]
## [1] "ITS2" "KLS0248"
##
## [[242]]
## [1] "ITS2" "KLS0253"
##
## [[243]]
## [1] "ITS2" "KLS0254"
##
## [[244]]
## [1] "ITS2" "KLS0256"
##
## [[245]]
## [1] "ITS2" "KLS0259"
##
## [[246]]
## [1] "ITS2" "KLS0263"
##
## [[247]]
## [1] "ITS2" "KLS0266"
##
## [[248]]
## [1] "ITS2" "KLS0272"
##
## [[249]]
## [1] "ITS2" "pcr" "its2" "neg" "ctrl" "20231021" "20231119"
##
## [[250]]
## [1] "ITS2" "pcr" "its2" "neg" "ctrl" "20231022" "20231120"
##
## [[251]]
## [1] "ITS2" "pcr" "its2" "neg" "ctrl" "20231023"
##
## [[252]]
## [1] "ITS2" "pcr" "its2" "neg" "ctrl" "20240411"
##
## [[253]]
## [1] "ITS2" "pcr" "its2" "neg" "ctrl" "20240416"
##
## [[254]]
## [1] "ITS2" "pcr" "its2" "neg" "ctrl" "20240417"
##
## [[255]]
## [1] "ITS2" "pcr" "its2" "neg" "ctrl" "20240418A"
##
## [[256]]
## [1] "ITS2" "pcr" "its2" "neg" "ctrl" "20240418B"
##
## [[257]]
## [1] "ITS2" "pcr" "its2" "neg" "ctrl" "20240517"
##
## [[258]]
## [1] "ITS2" "pcr" "its2" "neg" "ctrl" "20240524"
##
## [[259]]
## [1] "ITS2" "pcr" "its2" "neg" "ctrl" "Saskia" "20240411"
##
## [[260]]
## [1] "ITS2" "SCA0009"
##
## [[261]]
## [1] "ITS2" "SCA0010"
##
## [[262]]
## [1] "ITS2" "SCA0013" strsplit(sapply(strsplit(rownames(as.data.frame(out)), "_S"), function(l) l[[1]]),"-")[[1]][-1]## [1] "2020" "6" "16" "H1" temp<-strsplit(sapply(strsplit(rownames(as.data.frame(out)), "_S"), function(l) l[[1]]),"-")
sample.names<-character(length(rownames(as.data.frame(out)))) #set up container object
for(i in 1:length(rownames(as.data.frame(out)))){ #fill container with sample names
sample.names[i]<-paste(temp[[i]][-1],collapse="_")
}
head(sample.names); tail(sample.names); length(sample.names); length(rownames(out)) #sample.names, length of sample.names, length of samples output from filterAndTrim## [1] "2020_6_16_H1" "2020_6_16_H5" "2020_6_16_H6" "2020_6_17_H2" "2020_6_17_H4"
## [6] "2020_6_17_H8"## [1] "pcr_its2_neg_ctrl_20240517" "pcr_its2_neg_ctrl_20240524"
## [3] "pcr_its2_neg_ctrl_Saskia_20240411" "SCA0009"
## [5] "SCA0010" "SCA0013"## [1] 262## [1] 262rownames(out)<-sample.namesNot every sample made it through the filterAndTrim step
length(file.path(path.cut, "filtered", basename(cutFs))) #length of "filtFs," created in chunk above (262)## [1] 262length(list.files(file.path(path.cut, "filtered"), pattern = "L001_R1_001.fastq", full.names = TRUE)) #length of files actually written to the filtFs directories (254)## [1] 254Updating path names (after samples drop out)
# update directory, since not all samples made it thru the filter
filtFs <- file.path(path.cut, "filtered", basename(list.files(file.path(path.cut, "filtered"), pattern = "L001_R1_001.fastq", full.names = TRUE)))
filtRs <- file.path(path.cut, "filtered", basename(list.files(file.path(path.cut, "filtered"), pattern = "L001_R2_001.fastq", full.names = TRUE)))Learn error and inspect quality of cutadapted & filtered reads
##Learn the error rates Learns the error rates from an input list, or vector, of file names or a list of derep-class objects. Error rate estimation is performed by errorEstimationFunction. The output of this function serves as input to the dada function call as the err parameter
This uses the reads from the filter and trimmed files located in the “filtered” folder /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered
#You can safely ignore error messages “Not all sequences were the same length.”
errF <- learnErrors(filtFs, multithread = TRUE)## 104372214 total bases in 371645 reads from 35 samples will be used for learning the error rates.errR <- learnErrors(filtRs, multithread = TRUE)## 104475633 total bases in 371645 reads from 35 samples will be used for learning the error rates.#explanation of parameters in the learnErrors() function:
#learnErrors(
#fls, <-- fastq files
#nbases = 1e+08, <-- minimum number of total bases to learn error rate
#nreads = NULL, <-- deprecated, don't use
#errorEstimationFunction = loessErrfun,
#multithread = FALSE, <-- if enabled, sets the number of threads
#randomize = FALSE, <-- If FALSE, samples are read in the provided order until enough reads are obtained. If TRUE, samples are picked at random from those provided
#MAX_CONSIST = 10, <--The maximum number of times to step through the self-consistency loop.
#OMEGA_C = 0, <--The threshold at which unique sequences inferred to contain errors are corrected in the final output, and used to estimate the error rates
#qualityType = "Auto", <--The quality encoding of the fastq file(s). "Auto" (the default) means to attempt to auto-detect the encoding.
#verbose = FALSE)Plot errors
We expect a roughly linear decrease in Log transformed error frequency as the consensus quality score increases from 0 to 40
plotErrors(errF, nominalQ = TRUE) #forward## Warning in scale_y_log10(): log-10 transformation introduced infinite values.
plotErrors(errR, nominalQ = TRUE) #reverse## Warning in scale_y_log10(): log-10 transformation introduced infinite values.
Inspect read quality profiles
The quality profile plot is a gray-scale heatmap of the frequency of each quality score at each base position. The median quality score at each position is shown by the green line, and the quartiles of the quality score distribution by the orange lines. The read line shows the scaled proportion of reads that extend to at least that position.
plotQualityProfile(filtFs[n]) #inspect nth sample's forward reads
plotQualityProfile(filtRs[n]) #reverse always worse
Dereplication & denoising of identical sequences
Dereplication combines all identical sequencing reads into into “unique sequences” with a corresponding “abundance” (the number of reads with that same sequence). Dereplication substantially reduces computation time by eliminating redundant comparisons.
DADA2 retains a summary of the quality information associated with each unique sequence. The consensus quality profile of a unique sequence is the average of the positional qualities from the dereplicated reads. These quality profiles inform the error model of the subsequent denoising step, significantly increasing DADA2’s accuracy. But we did the learnErrors step before dereplication? dada is the denoising step and uses the error model created before
using the reads from the filter and trimmed files located in the “filtered” folder /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered
##Dereplicate reads
derepFs <- derepFastq(filtFs, verbose = TRUE)## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-16-H1_S31_L001_R1_001.fastq## Encountered 2 unique sequences from 2 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-16-H5_S32_L001_R1_001.fastq## Encountered 3 unique sequences from 3 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-16-H6_S33_L001_R1_001.fastq## Encountered 1 unique sequences from 1 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-17-H2_S34_L001_R1_001.fastq## Encountered 7 unique sequences from 7 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-17-H4_S35_L001_R1_001.fastq## Encountered 8 unique sequences from 8 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-17-H8_S36_L001_R1_001.fastq## Encountered 5 unique sequences from 5 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-18-H3_S37_L001_R1_001.fastq## Encountered 6411 unique sequences from 28544 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-18-H7_S38_L001_R1_001.fastq## Encountered 3101 unique sequences from 14114 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-18-H9_S39_L001_R1_001.fastq## Encountered 2768 unique sequences from 9775 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-3-H1_S40_L001_R1_001.fastq## Encountered 4015 unique sequences from 17562 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-3-H5_S41_L001_R1_001.fastq## Encountered 3747 unique sequences from 17183 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-3-H6_S42_L001_R1_001.fastq## Encountered 2460 unique sequences from 9113 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-30-H1_S43_L001_R1_001.fastq## Encountered 3335 unique sequences from 11400 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-30-H6_S45_L001_R1_001.fastq## Encountered 1 unique sequences from 1 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-4-H2_S46_L001_R1_001.fastq## Encountered 1627 unique sequences from 3807 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-4-H4_S47_L001_R1_001.fastq## Encountered 2493 unique sequences from 7207 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-4-H8_S48_L001_R1_001.fastq## Encountered 4403 unique sequences from 20412 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-5-H3_S49_L001_R1_001.fastq## Encountered 3161 unique sequences from 13330 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-5-H7_S50_L001_R1_001.fastq## Encountered 3277 unique sequences from 13763 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-5-H9_S51_L001_R1_001.fastq## Encountered 2 unique sequences from 2 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-1-H2_S52_L001_R1_001.fastq## Encountered 1 unique sequences from 1 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-1-H4_S53_L001_R1_001.fastq## Encountered 3 unique sequences from 3 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-1-H8_S54_L001_R1_001.fastq## Encountered 8478 unique sequences from 59663 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-14-H1_S55_L001_R1_001.fastq## Encountered 24 unique sequences from 54 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-14-H5_S56_L001_R1_001.fastq## Encountered 6274 unique sequences from 25171 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-14-H6_S57_L001_R1_001.fastq## Encountered 5803 unique sequences from 25820 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-15-H4_S59_L001_R1_001.fastq## Encountered 4 unique sequences from 4 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-15-H8_S60_L001_R1_001.fastq## Encountered 3 unique sequences from 3 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-16-H3_S61_L001_R1_001.fastq## Encountered 4 unique sequences from 4 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-16-H9_S63_L001_R1_001.fastq## Encountered 2 unique sequences from 2 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-2-H3_S64_L001_R1_001.fastq## Encountered 5547 unique sequences from 19284 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-2-H7_S65_L001_R1_001.fastq## Encountered 4022 unique sequences from 14455 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-2-H9_S66_L001_R1_001.fastq## Encountered 2140 unique sequences from 7696 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-13-H1_S67_L001_R1_001.fastq## Encountered 5141 unique sequences from 33662 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-13-H3_S68_L001_R1_001.fastq## Encountered 4338 unique sequences from 19584 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-14-H11_S69_L001_R1_001.fastq## Encountered 5338 unique sequences from 30473 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-14-H6_S70_L001_R1_001.fastq## Encountered 4070 unique sequences from 21451 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-14-H7_S71_L001_R1_001.fastq## Encountered 4454 unique sequences from 27667 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-15-H8_S72_L001_R1_001.fastq## Encountered 5768 unique sequences from 29183 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-21-H10_S73_L001_R1_001.fastq## Encountered 4572 unique sequences from 22468 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-21-H12_S74_L001_R1_001.fastq## Encountered 2949 unique sequences from 15386 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-21-H9_S75_L001_R1_001.fastq## Encountered 4394 unique sequences from 22706 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-27-H21_S76_L001_R1_001.fastq## Encountered 3341 unique sequences from 13598 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-27-H22_S77_L001_R1_001.fastq## Encountered 2965 unique sequences from 16586 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-27-H27_S78_L001_R1_001.fastq## Encountered 2829 unique sequences from 11031 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-28-H25_S79_L001_R1_001.fastq## Encountered 6110 unique sequences from 37109 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-28-H26_S80_L001_R1_001.fastq## Encountered 4087 unique sequences from 18011 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-28-H28_S81_L001_R1_001.fastq## Encountered 7181 unique sequences from 24520 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-29-H17_S82_L001_R1_001.fastq## Encountered 4809 unique sequences from 20380 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-29-H23_S83_L001_R1_001.fastq## Encountered 3259 unique sequences from 15119 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-29-H24_S84_L001_R1_001.fastq## Encountered 4177 unique sequences from 23804 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-4-H21_S85_L001_R1_001.fastq## Encountered 2410 unique sequences from 7846 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-4-H22_S86_L001_R1_001.fastq## Encountered 5726 unique sequences from 32343 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-4-H27_S87_L001_R1_001.fastq## Encountered 1388 unique sequences from 4382 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-5-H18_S88_L001_R1_001.fastq## Encountered 2268 unique sequences from 8700 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-5-H25_S89_L001_R1_001.fastq## Encountered 1757 unique sequences from 6167 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-5-H26_S90_L001_R1_001.fastq## Encountered 6992 unique sequences from 30751 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-6-H17_S91_L001_R1_001.fastq## Encountered 2556 unique sequences from 9885 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-6-H24_S92_L001_R1_001.fastq## Encountered 5879 unique sequences from 27479 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-7-H23_S93_L001_R1_001.fastq## Encountered 2630 unique sequences from 10700 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-14-H10_S94_L001_R1_001.fastq## Encountered 2867 unique sequences from 17609 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-20-H27_S96_L001_R1_001.fastq## Encountered 3138 unique sequences from 12038 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-21-H25_S97_L001_R1_001.fastq## Encountered 3041 unique sequences from 16172 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-21-H26_S98_L001_R1_001.fastq## Encountered 6 unique sequences from 6 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-21-H28_S99_L001_R1_001.fastq## Encountered 2 unique sequences from 2 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-6-H11_S100_L001_R1_001.fastq## Encountered 6533 unique sequences from 23260 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-6-H30_S101_L001_R1_001.fastq## Encountered 1 unique sequences from 1 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-6-H6_S102_L001_R1_001.fastq## Encountered 3537 unique sequences from 12438 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-7-H8_S104_L001_R1_001.fastq## Encountered 3627 unique sequences from 23534 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-8-H3_S105_L001_R1_001.fastq## Encountered 4064 unique sequences from 23041 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-12-H3_S106_L001_R1_001.fastq## Encountered 2883 unique sequences from 12263 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-12-H5_S107_L001_R1_001.fastq## Encountered 4865 unique sequences from 24829 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-12-H7_S108_L001_R1_001.fastq## Encountered 1895 unique sequences from 6086 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-13-H6_S109_L001_R1_001.fastq## Encountered 2828 unique sequences from 13625 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-13-H8_S110_L001_R1_001.fastq## Encountered 3772 unique sequences from 15490 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-13-H9_S111_L001_R1_001.fastq## Encountered 3407 unique sequences from 19503 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-14-H3_S112_L001_R1_001.fastq## Encountered 3942 unique sequences from 20699 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-14-H7_S113_L001_R1_001.fastq## Encountered 6335 unique sequences from 33188 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-14-H9_S114_L001_R1_001.fastq## Encountered 6508 unique sequences from 37485 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-16-H5_S115_L001_R1_001.fastq## Encountered 3705 unique sequences from 15022 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-24-H6_S116_L001_R1_001.fastq## Encountered 7751 unique sequences from 34675 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-24-H8_S117_L001_R1_001.fastq## Encountered 4903 unique sequences from 17439 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-25-H2_S118_L001_R1_001.fastq## Encountered 7986 unique sequences from 31265 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-25-H4_S119_L001_R1_001.fastq## Encountered 6969 unique sequences from 31537 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-26-H1_S120_L001_R1_001.fastq## Encountered 3225 unique sequences from 8136 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-26-H7_S121_L001_R1_001.fastq## Encountered 5999 unique sequences from 24821 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-27-H3_S122_L001_R1_001.fastq## Encountered 2902 unique sequences from 10606 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-27-H5_S123_L001_R1_001.fastq## Encountered 4567 unique sequences from 16479 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-8-H1_S124_L001_R1_001.fastq## Encountered 5088 unique sequences from 21254 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-8-H2_S125_L001_R1_001.fastq## Encountered 3050 unique sequences from 16527 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-8-H4_S126_L001_R1_001.fastq## Encountered 5349 unique sequences from 38333 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-9-H2_S127_L001_R1_001.fastq## Encountered 3228 unique sequences from 14590 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-9-H4_S128_L001_R1_001.fastq## Encountered 4381 unique sequences from 22545 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-15-H6_S129_L001_R1_001.fastq## Encountered 5373 unique sequences from 23983 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-16-H4_S130_L001_R1_001.fastq## Encountered 5533 unique sequences from 29295 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-17-H1_S131_L001_R1_001.fastq## Encountered 3654 unique sequences from 14894 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-18-H3_S132_L001_R1_001.fastq## Encountered 5279 unique sequences from 21650 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-18-H7_S133_L001_R1_001.fastq## Encountered 2367 unique sequences from 12527 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-29-H5_S134_L001_R1_001.fastq## Encountered 5393 unique sequences from 25406 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-29-H7_S135_L001_R1_001.fastq## Encountered 7171 unique sequences from 40098 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-30-H8_S136_L001_R1_001.fastq## Encountered 5008 unique sequences from 27389 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-30-H9_S137_L001_R1_001.fastq## Encountered 7051 unique sequences from 42773 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-5-H1_S138_L001_R1_001.fastq## Encountered 3099 unique sequences from 18663 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-5-H2_S139_L001_R1_001.fastq## Encountered 3874 unique sequences from 24683 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-5-H4_S140_L001_R1_001.fastq## Encountered 2963 unique sequences from 16886 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-6-H6_S141_L001_R1_001.fastq## Encountered 3889 unique sequences from 23320 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-6-H8_S142_L001_R1_001.fastq## Encountered 4410 unique sequences from 25858 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-6-H9_S143_L001_R1_001.fastq## Encountered 6979 unique sequences from 37973 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-8-H3_S144_L001_R1_001.fastq## Encountered 2995 unique sequences from 14762 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-8-H5_S145_L001_R1_001.fastq## Encountered 2382 unique sequences from 16132 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-8-H7_S146_L001_R1_001.fastq## Encountered 4194 unique sequences from 24378 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H2_S147_L001_R1_001.fastq## Encountered 3737 unique sequences from 23680 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H5_S148_L001_R1_001.fastq## Encountered 7584 unique sequences from 34917 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H6_S149_L001_R1_001.fastq## Encountered 3819 unique sequences from 15791 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H7_S150_L001_R1_001.fastq## Encountered 5292 unique sequences from 19770 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H8_S151_L001_R1_001.fastq## Encountered 4401 unique sequences from 17643 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H9_S152_L001_R1_001.fastq## Encountered 4314 unique sequences from 14039 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Ba001_S153_L001_R1_001.fastq## Encountered 3129 unique sequences from 10777 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Ba002_S154_L001_R1_001.fastq## Encountered 1886 unique sequences from 5537 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Ba003_S155_L001_R1_001.fastq## Encountered 3998 unique sequences from 9074 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb001_S156_L001_R1_001.fastq## Encountered 1888 unique sequences from 6275 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb002_S157_L001_R1_001.fastq## Encountered 2159 unique sequences from 7357 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb003_S158_L001_R1_001.fastq## Encountered 3197 unique sequences from 11309 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb004_S159_L001_R1_001.fastq## Encountered 3109 unique sequences from 10220 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb005_S160_L001_R1_001.fastq## Encountered 1556 unique sequences from 5421 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb007_S161_L001_R1_001.fastq## Encountered 309 unique sequences from 1227 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb008_S162_L001_R1_001.fastq## Encountered 884 unique sequences from 3419 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb009_S163_L001_R1_001.fastq## Encountered 585 unique sequences from 2193 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb010_S164_L001_R1_001.fastq## Encountered 3182 unique sequences from 8989 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb011_S165_L001_R1_001.fastq## Encountered 1819 unique sequences from 5075 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb012_S166_L001_R1_001.fastq## Encountered 3718 unique sequences from 15928 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb013_S167_L001_R1_001.fastq## Encountered 2077 unique sequences from 6123 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb014_S168_L001_R1_001.fastq## Encountered 1087 unique sequences from 3127 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb015_S169_L001_R1_001.fastq## Encountered 1103 unique sequences from 3045 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb016_S170_L001_R1_001.fastq## Encountered 124 unique sequences from 318 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb017_S171_L001_R1_001.fastq## Encountered 742 unique sequences from 2279 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb018_S172_L001_R1_001.fastq## Encountered 2031 unique sequences from 5380 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb019_S173_L001_R1_001.fastq## Encountered 2438 unique sequences from 8859 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb020_S174_L001_R1_001.fastq## Encountered 1302 unique sequences from 6218 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb021_S175_L001_R1_001.fastq## Encountered 4100 unique sequences from 13981 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb022_S176_L001_R1_001.fastq## Encountered 5105 unique sequences from 24593 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb023_S177_L001_R1_001.fastq## Encountered 4617 unique sequences from 24923 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb024_S178_L001_R1_001.fastq## Encountered 5541 unique sequences from 36400 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb025_S179_L001_R1_001.fastq## Encountered 3804 unique sequences from 16550 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bf001_S180_L001_R1_001.fastq## Encountered 3964 unique sequences from 22204 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bf002_S181_L001_R1_001.fastq## Encountered 3447 unique sequences from 18314 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bf003_S182_L001_R1_001.fastq## Encountered 4327 unique sequences from 28486 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bf004_S183_L001_R1_001.fastq## Encountered 4943 unique sequences from 20792 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg001_S184_L001_R1_001.fastq## Encountered 5227 unique sequences from 19460 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg002_S185_L001_R1_001.fastq## Encountered 4239 unique sequences from 14410 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg003_S186_L001_R1_001.fastq## Encountered 7289 unique sequences from 31643 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg004_S187_L001_R1_001.fastq## Encountered 6501 unique sequences from 21133 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg005_S188_L001_R1_001.fastq## Encountered 4026 unique sequences from 18459 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg006_S189_L001_R1_001.fastq## Encountered 7585 unique sequences from 30218 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg007_S190_L001_R1_001.fastq## Encountered 3071 unique sequences from 14612 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg008_S191_L001_R1_001.fastq## Encountered 3225 unique sequences from 12218 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg009_S192_L001_R1_001.fastq## Encountered 5073 unique sequences from 21107 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg010_S193_L001_R1_001.fastq## Encountered 7453 unique sequences from 35028 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg011_S194_L001_R1_001.fastq## Encountered 5894 unique sequences from 25569 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg012_S195_L001_R1_001.fastq## Encountered 6000 unique sequences from 32557 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg013_S196_L001_R1_001.fastq## Encountered 2861 unique sequences from 11893 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg014_S197_L001_R1_001.fastq## Encountered 3897 unique sequences from 23693 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg015_S198_L001_R1_001.fastq## Encountered 3853 unique sequences from 17641 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg016_S199_L001_R1_001.fastq## Encountered 2884 unique sequences from 15525 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg017_S200_L001_R1_001.fastq## Encountered 3301 unique sequences from 12481 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg018_S201_L001_R1_001.fastq## Encountered 4173 unique sequences from 18766 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg019_S202_L001_R1_001.fastq## Encountered 3954 unique sequences from 16055 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi001_S203_L001_R1_001.fastq## Encountered 4028 unique sequences from 17384 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi002_S204_L001_R1_001.fastq## Encountered 4085 unique sequences from 19912 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi003_S205_L001_R1_001.fastq## Encountered 2940 unique sequences from 12910 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi004_S206_L001_R1_001.fastq## Encountered 6901 unique sequences from 42207 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi005_S207_L001_R1_001.fastq## Encountered 42 unique sequences from 111 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi006_S208_L001_R1_001.fastq## Encountered 7463 unique sequences from 38312 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi007_S209_L001_R1_001.fastq## Encountered 6608 unique sequences from 30085 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-CKC0001_S210_L001_R1_001.fastq## Encountered 1793 unique sequences from 9923 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ESE0004_S211_L001_R1_001.fastq## Encountered 3591 unique sequences from 11887 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20230909_S212_L001_R1_001.fastq## Encountered 18 unique sequences from 33 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20230923_S213_L001_R1_001.fastq## Encountered 1 unique sequences from 1 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20230924_S214_L001_R1_001.fastq## Encountered 5 unique sequences from 5 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20231007_S215_L001_R1_001.fastq## Encountered 3 unique sequences from 3 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20231008_S216_L001_R1_001.fastq## Encountered 11 unique sequences from 50 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20231009_S217_L001_R1_001.fastq## Encountered 89 unique sequences from 358 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024220A_S218_L001_R1_001.fastq## Encountered 59 unique sequences from 131 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024220B_S219_L001_R1_001.fastq## Encountered 50 unique sequences from 129 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024221A_S220_L001_R1_001.fastq## Encountered 60 unique sequences from 159 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024221B_S221_L001_R1_001.fastq## Encountered 57 unique sequences from 130 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024222A_S222_L001_R1_001.fastq## Encountered 56 unique sequences from 88 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024222B_S223_L001_R1_001.fastq## Encountered 16 unique sequences from 76 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024312A_S224_L001_R1_001.fastq## Encountered 42 unique sequences from 104 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024312B_S225_L001_R1_001.fastq## Encountered 14 unique sequences from 28 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024314A_S226_L001_R1_001.fastq## Encountered 1 unique sequences from 1 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024319_S228_L001_R1_001.fastq## Encountered 6 unique sequences from 6 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024320_S229_L001_R1_001.fastq## Encountered 14 unique sequences from 21 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0007_S230_L001_R1_001.fastq## Encountered 1549 unique sequences from 4798 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0027_S232_L001_R1_001.fastq## Encountered 1367 unique sequences from 5767 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0044_S233_L001_R1_001.fastq## Encountered 2375 unique sequences from 8955 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0045_S234_L001_R1_001.fastq## Encountered 1735 unique sequences from 6222 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0052_S235_L001_R1_001.fastq## Encountered 1671 unique sequences from 5529 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0054_S236_L001_R1_001.fastq## Encountered 2838 unique sequences from 16389 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0055_S237_L001_R1_001.fastq## Encountered 2381 unique sequences from 15797 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0071_S238_L001_R1_001.fastq## Encountered 3053 unique sequences from 11709 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0095_S239_L001_R1_001.fastq## Encountered 1744 unique sequences from 8701 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0096_S240_L001_R1_001.fastq## Encountered 3288 unique sequences from 14500 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0105_S241_L001_R1_001.fastq## Encountered 2875 unique sequences from 19463 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0106_S242_L001_R1_001.fastq## Encountered 1697 unique sequences from 5682 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0119_S243_L001_R1_001.fastq## Encountered 3772 unique sequences from 12665 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0134_S244_L001_R1_001.fastq## Encountered 2561 unique sequences from 11447 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0135_S245_L001_R1_001.fastq## Encountered 2014 unique sequences from 8081 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0136_S246_L001_R1_001.fastq## Encountered 874 unique sequences from 2509 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0137_S247_L001_R1_001.fastq## Encountered 1570 unique sequences from 4076 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0138_S248_L001_R1_001.fastq## Encountered 1459 unique sequences from 6754 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0139_S249_L001_R1_001.fastq## Encountered 2528 unique sequences from 10020 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0150_S250_L001_R1_001.fastq## Encountered 3695 unique sequences from 18611 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0153_S251_L001_R1_001.fastq## Encountered 1396 unique sequences from 4536 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0155_S252_L001_R1_001.fastq## Encountered 3534 unique sequences from 17599 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0156_S253_L001_R1_001.fastq## Encountered 2899 unique sequences from 12671 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0159_S254_L001_R1_001.fastq## Encountered 2257 unique sequences from 9988 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0163_S255_L001_R1_001.fastq## Encountered 2567 unique sequences from 9958 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0165_S256_L001_R1_001.fastq## Encountered 3012 unique sequences from 12110 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0167_S257_L001_R1_001.fastq## Encountered 2650 unique sequences from 9019 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0168_S258_L001_R1_001.fastq## Encountered 1809 unique sequences from 7722 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0169_S259_L001_R1_001.fastq## Encountered 2530 unique sequences from 8051 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0170_S260_L001_R1_001.fastq## Encountered 2997 unique sequences from 9209 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0200_S261_L001_R1_001.fastq## Encountered 1628 unique sequences from 8381 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0201_S262_L001_R1_001.fastq## Encountered 7103 unique sequences from 26461 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0205_S263_L001_R1_001.fastq## Encountered 2735 unique sequences from 8493 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0209_S264_L001_R1_001.fastq## Encountered 3356 unique sequences from 14812 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0221_S265_L001_R1_001.fastq## Encountered 4243 unique sequences from 20667 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0224_S266_L001_R1_001.fastq## Encountered 1922 unique sequences from 5175 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0225_S267_L001_R1_001.fastq## Encountered 2717 unique sequences from 11502 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0227_S268_L001_R1_001.fastq## Encountered 2383 unique sequences from 11615 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0241_S269_L001_R1_001.fastq## Encountered 1827 unique sequences from 10364 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0244_S270_L001_R1_001.fastq## Encountered 1098 unique sequences from 2924 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0246_S271_L001_R1_001.fastq## Encountered 1639 unique sequences from 4743 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0248_S272_L001_R1_001.fastq## Encountered 1900 unique sequences from 9660 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0253_S273_L001_R1_001.fastq## Encountered 1963 unique sequences from 6275 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0254_S274_L001_R1_001.fastq## Encountered 4974 unique sequences from 22985 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0256_S231_L001_R1_001.fastq## Encountered 2012 unique sequences from 7938 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0259_S275_L001_R1_001.fastq## Encountered 3905 unique sequences from 19483 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0263_S276_L001_R1_001.fastq## Encountered 2845 unique sequences from 11532 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0272_S278_L001_R1_001.fastq## Encountered 3381 unique sequences from 12275 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20231021-20231119_S279_L001_R1_001.fastq## Encountered 7 unique sequences from 7 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20231022-20231120_S280_L001_R1_001.fastq## Encountered 1 unique sequences from 1 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20231023_S281_L001_R1_001.fastq## Encountered 8 unique sequences from 12 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240411_S282_L001_R1_001.fastq## Encountered 5 unique sequences from 5 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240417_S284_L001_R1_001.fastq## Encountered 110 unique sequences from 260 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240418A_S285_L001_R1_001.fastq## Encountered 103 unique sequences from 309 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240418B_S286_L001_R1_001.fastq## Encountered 32 unique sequences from 61 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240517_S287_L001_R1_001.fastq## Encountered 10 unique sequences from 33 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240524_S288_L001_R1_001.fastq## Encountered 1 unique sequences from 2 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-Saskia-20240411_S289_L001_R1_001.fastq## Encountered 2 unique sequences from 2 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-SCA0009_S290_L001_R1_001.fastq## Encountered 3854 unique sequences from 12498 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-SCA0010_S291_L001_R1_001.fastq## Encountered 3950 unique sequences from 13374 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-SCA0013_S292_L001_R1_001.fastq## Encountered 2230 unique sequences from 6844 total sequences read.derepRs <- derepFastq(filtRs, verbose = TRUE)## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-16-H1_S31_L001_R2_001.fastq## Encountered 2 unique sequences from 2 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-16-H5_S32_L001_R2_001.fastq## Encountered 3 unique sequences from 3 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-16-H6_S33_L001_R2_001.fastq## Encountered 1 unique sequences from 1 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-17-H2_S34_L001_R2_001.fastq## Encountered 7 unique sequences from 7 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-17-H4_S35_L001_R2_001.fastq## Encountered 8 unique sequences from 8 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-17-H8_S36_L001_R2_001.fastq## Encountered 5 unique sequences from 5 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-18-H3_S37_L001_R2_001.fastq## Encountered 20651 unique sequences from 28544 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-18-H7_S38_L001_R2_001.fastq## Encountered 9292 unique sequences from 14114 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-18-H9_S39_L001_R2_001.fastq## Encountered 8987 unique sequences from 9775 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-3-H1_S40_L001_R2_001.fastq## Encountered 12234 unique sequences from 17562 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-3-H5_S41_L001_R2_001.fastq## Encountered 12653 unique sequences from 17183 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-3-H6_S42_L001_R2_001.fastq## Encountered 7680 unique sequences from 9113 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-30-H1_S43_L001_R2_001.fastq## Encountered 8576 unique sequences from 11400 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-30-H6_S45_L001_R2_001.fastq## Encountered 1 unique sequences from 1 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-4-H2_S46_L001_R2_001.fastq## Encountered 3775 unique sequences from 3807 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-4-H4_S47_L001_R2_001.fastq## Encountered 6335 unique sequences from 7207 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-4-H8_S48_L001_R2_001.fastq## Encountered 14856 unique sequences from 20412 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-5-H3_S49_L001_R2_001.fastq## Encountered 9488 unique sequences from 13330 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-5-H7_S50_L001_R2_001.fastq## Encountered 9633 unique sequences from 13763 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-6-5-H9_S51_L001_R2_001.fastq## Encountered 2 unique sequences from 2 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-1-H2_S52_L001_R2_001.fastq## Encountered 1 unique sequences from 1 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-1-H4_S53_L001_R2_001.fastq## Encountered 3 unique sequences from 3 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-1-H8_S54_L001_R2_001.fastq## Encountered 37458 unique sequences from 59663 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-14-H1_S55_L001_R2_001.fastq## Encountered 52 unique sequences from 54 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-14-H5_S56_L001_R2_001.fastq## Encountered 21493 unique sequences from 25171 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-14-H6_S57_L001_R2_001.fastq## Encountered 18015 unique sequences from 25820 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-15-H4_S59_L001_R2_001.fastq## Encountered 4 unique sequences from 4 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-15-H8_S60_L001_R2_001.fastq## Encountered 3 unique sequences from 3 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-16-H3_S61_L001_R2_001.fastq## Encountered 4 unique sequences from 4 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-16-H9_S63_L001_R2_001.fastq## Encountered 2 unique sequences from 2 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-2-H3_S64_L001_R2_001.fastq## Encountered 13885 unique sequences from 19284 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-2-H7_S65_L001_R2_001.fastq## Encountered 11100 unique sequences from 14455 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2020-7-2-H9_S66_L001_R2_001.fastq## Encountered 5723 unique sequences from 7696 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-13-H1_S67_L001_R2_001.fastq## Encountered 18255 unique sequences from 33662 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-13-H3_S68_L001_R2_001.fastq## Encountered 13414 unique sequences from 19584 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-14-H11_S69_L001_R2_001.fastq## Encountered 17392 unique sequences from 30473 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-14-H6_S70_L001_R2_001.fastq## Encountered 15131 unique sequences from 21451 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-14-H7_S71_L001_R2_001.fastq## Encountered 15157 unique sequences from 27667 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-15-H8_S72_L001_R2_001.fastq## Encountered 18315 unique sequences from 29183 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-21-H10_S73_L001_R2_001.fastq## Encountered 16215 unique sequences from 22468 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-21-H12_S74_L001_R2_001.fastq## Encountered 9976 unique sequences from 15386 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-21-H9_S75_L001_R2_001.fastq## Encountered 16545 unique sequences from 22706 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-27-H21_S76_L001_R2_001.fastq## Encountered 10501 unique sequences from 13598 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-27-H22_S77_L001_R2_001.fastq## Encountered 9094 unique sequences from 16586 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-27-H27_S78_L001_R2_001.fastq## Encountered 8284 unique sequences from 11031 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-28-H25_S79_L001_R2_001.fastq## Encountered 23005 unique sequences from 37109 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-28-H26_S80_L001_R2_001.fastq## Encountered 14602 unique sequences from 18011 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-28-H28_S81_L001_R2_001.fastq## Encountered 19816 unique sequences from 24520 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-29-H17_S82_L001_R2_001.fastq## Encountered 14096 unique sequences from 20380 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-29-H23_S83_L001_R2_001.fastq## Encountered 10484 unique sequences from 15119 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-29-H24_S84_L001_R2_001.fastq## Encountered 14554 unique sequences from 23804 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-4-H21_S85_L001_R2_001.fastq## Encountered 7481 unique sequences from 7846 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-4-H22_S86_L001_R2_001.fastq## Encountered 25806 unique sequences from 32343 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-4-H27_S87_L001_R2_001.fastq## Encountered 4201 unique sequences from 4382 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-5-H18_S88_L001_R2_001.fastq## Encountered 7890 unique sequences from 8700 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-5-H25_S89_L001_R2_001.fastq## Encountered 5707 unique sequences from 6167 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-5-H26_S90_L001_R2_001.fastq## Encountered 21761 unique sequences from 30751 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-6-H17_S91_L001_R2_001.fastq## Encountered 8981 unique sequences from 9885 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-6-H24_S92_L001_R2_001.fastq## Encountered 20131 unique sequences from 27479 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-6-7-H23_S93_L001_R2_001.fastq## Encountered 10106 unique sequences from 10700 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-14-H10_S94_L001_R2_001.fastq## Encountered 12430 unique sequences from 17609 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-20-H27_S96_L001_R2_001.fastq## Encountered 10588 unique sequences from 12038 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-21-H25_S97_L001_R2_001.fastq## Encountered 9763 unique sequences from 16172 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-21-H26_S98_L001_R2_001.fastq## Encountered 6 unique sequences from 6 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-21-H28_S99_L001_R2_001.fastq## Encountered 2 unique sequences from 2 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-6-H11_S100_L001_R2_001.fastq## Encountered 16302 unique sequences from 23260 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-6-H30_S101_L001_R2_001.fastq## Encountered 1 unique sequences from 1 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-6-H6_S102_L001_R2_001.fastq## Encountered 9380 unique sequences from 12438 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-7-H8_S104_L001_R2_001.fastq## Encountered 12352 unique sequences from 23534 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2021-7-8-H3_S105_L001_R2_001.fastq## Encountered 13309 unique sequences from 23041 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-12-H3_S106_L001_R2_001.fastq## Encountered 8624 unique sequences from 12263 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-12-H5_S107_L001_R2_001.fastq## Encountered 17396 unique sequences from 24829 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-12-H7_S108_L001_R2_001.fastq## Encountered 5638 unique sequences from 6086 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-13-H6_S109_L001_R2_001.fastq## Encountered 9379 unique sequences from 13625 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-13-H8_S110_L001_R2_001.fastq## Encountered 11650 unique sequences from 15490 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-13-H9_S111_L001_R2_001.fastq## Encountered 12010 unique sequences from 19503 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-14-H3_S112_L001_R2_001.fastq## Encountered 13041 unique sequences from 20699 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-14-H7_S113_L001_R2_001.fastq## Encountered 21643 unique sequences from 33188 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-14-H9_S114_L001_R2_001.fastq## Encountered 22444 unique sequences from 37485 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-16-H5_S115_L001_R2_001.fastq## Encountered 13802 unique sequences from 15022 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-24-H6_S116_L001_R2_001.fastq## Encountered 26469 unique sequences from 34675 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-24-H8_S117_L001_R2_001.fastq## Encountered 13441 unique sequences from 17439 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-25-H2_S118_L001_R2_001.fastq## Encountered 23138 unique sequences from 31265 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-25-H4_S119_L001_R2_001.fastq## Encountered 22363 unique sequences from 31537 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-26-H1_S120_L001_R2_001.fastq## Encountered 6823 unique sequences from 8136 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-26-H7_S121_L001_R2_001.fastq## Encountered 18833 unique sequences from 24821 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-27-H3_S122_L001_R2_001.fastq## Encountered 7990 unique sequences from 10606 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-27-H5_S123_L001_R2_001.fastq## Encountered 12619 unique sequences from 16479 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-8-H1_S124_L001_R2_001.fastq## Encountered 14780 unique sequences from 21254 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-8-H2_S125_L001_R2_001.fastq## Encountered 9264 unique sequences from 16527 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-8-H4_S126_L001_R2_001.fastq## Encountered 23279 unique sequences from 38333 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-9-H2_S127_L001_R2_001.fastq## Encountered 10008 unique sequences from 14590 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-6-9-H4_S128_L001_R2_001.fastq## Encountered 14492 unique sequences from 22545 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-15-H6_S129_L001_R2_001.fastq## Encountered 19089 unique sequences from 23983 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-16-H4_S130_L001_R2_001.fastq## Encountered 24471 unique sequences from 29295 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-17-H1_S131_L001_R2_001.fastq## Encountered 12485 unique sequences from 14894 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-18-H3_S132_L001_R2_001.fastq## Encountered 15401 unique sequences from 21650 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-18-H7_S133_L001_R2_001.fastq## Encountered 10946 unique sequences from 12527 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-29-H5_S134_L001_R2_001.fastq## Encountered 18471 unique sequences from 25406 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-29-H7_S135_L001_R2_001.fastq## Encountered 23929 unique sequences from 40098 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-30-H8_S136_L001_R2_001.fastq## Encountered 17741 unique sequences from 27389 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-30-H9_S137_L001_R2_001.fastq## Encountered 30297 unique sequences from 42773 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-5-H1_S138_L001_R2_001.fastq## Encountered 10825 unique sequences from 18663 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-5-H2_S139_L001_R2_001.fastq## Encountered 16829 unique sequences from 24683 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-5-H4_S140_L001_R2_001.fastq## Encountered 12554 unique sequences from 16886 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-6-H6_S141_L001_R2_001.fastq## Encountered 16740 unique sequences from 23320 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-6-H8_S142_L001_R2_001.fastq## Encountered 18169 unique sequences from 25858 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-6-H9_S143_L001_R2_001.fastq## Encountered 24915 unique sequences from 37973 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-8-H3_S144_L001_R2_001.fastq## Encountered 10851 unique sequences from 14762 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-8-H5_S145_L001_R2_001.fastq## Encountered 13001 unique sequences from 16132 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-7-8-H7_S146_L001_R2_001.fastq## Encountered 18245 unique sequences from 24378 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H2_S147_L001_R2_001.fastq## Encountered 14175 unique sequences from 23680 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H5_S148_L001_R2_001.fastq## Encountered 25007 unique sequences from 34917 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H6_S149_L001_R2_001.fastq## Encountered 12933 unique sequences from 15791 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H7_S150_L001_R2_001.fastq## Encountered 15802 unique sequences from 19770 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H8_S151_L001_R2_001.fastq## Encountered 12828 unique sequences from 17643 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-2023-8-4-H9_S152_L001_R2_001.fastq## Encountered 10897 unique sequences from 14039 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Ba001_S153_L001_R2_001.fastq## Encountered 9564 unique sequences from 10777 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Ba002_S154_L001_R2_001.fastq## Encountered 4555 unique sequences from 5537 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Ba003_S155_L001_R2_001.fastq## Encountered 8468 unique sequences from 9074 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb001_S156_L001_R2_001.fastq## Encountered 5272 unique sequences from 6275 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb002_S157_L001_R2_001.fastq## Encountered 6020 unique sequences from 7357 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb003_S158_L001_R2_001.fastq## Encountered 9127 unique sequences from 11309 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb004_S159_L001_R2_001.fastq## Encountered 8578 unique sequences from 10220 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb005_S160_L001_R2_001.fastq## Encountered 4481 unique sequences from 5421 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb007_S161_L001_R2_001.fastq## Encountered 896 unique sequences from 1227 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb008_S162_L001_R2_001.fastq## Encountered 2604 unique sequences from 3419 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb009_S163_L001_R2_001.fastq## Encountered 1601 unique sequences from 2193 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb010_S164_L001_R2_001.fastq## Encountered 8187 unique sequences from 8989 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb011_S165_L001_R2_001.fastq## Encountered 4100 unique sequences from 5075 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb012_S166_L001_R2_001.fastq## Encountered 11477 unique sequences from 15928 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb013_S167_L001_R2_001.fastq## Encountered 5391 unique sequences from 6123 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb014_S168_L001_R2_001.fastq## Encountered 2729 unique sequences from 3127 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb015_S169_L001_R2_001.fastq## Encountered 2477 unique sequences from 3045 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb016_S170_L001_R2_001.fastq## Encountered 291 unique sequences from 318 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb017_S171_L001_R2_001.fastq## Encountered 1751 unique sequences from 2279 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb018_S172_L001_R2_001.fastq## Encountered 4355 unique sequences from 5380 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb019_S173_L001_R2_001.fastq## Encountered 6953 unique sequences from 8859 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb020_S174_L001_R2_001.fastq## Encountered 5238 unique sequences from 6218 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb021_S175_L001_R2_001.fastq## Encountered 12357 unique sequences from 13981 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb022_S176_L001_R2_001.fastq## Encountered 17515 unique sequences from 24593 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb023_S177_L001_R2_001.fastq## Encountered 19635 unique sequences from 24923 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb024_S178_L001_R2_001.fastq## Encountered 20105 unique sequences from 36400 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bb025_S179_L001_R2_001.fastq## Encountered 11672 unique sequences from 16550 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bf001_S180_L001_R2_001.fastq## Encountered 18751 unique sequences from 22204 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bf002_S181_L001_R2_001.fastq## Encountered 13171 unique sequences from 18314 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bf003_S182_L001_R2_001.fastq## Encountered 21411 unique sequences from 28486 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bf004_S183_L001_R2_001.fastq## Encountered 16159 unique sequences from 20792 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg001_S184_L001_R2_001.fastq## Encountered 15587 unique sequences from 19460 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg002_S185_L001_R2_001.fastq## Encountered 11341 unique sequences from 14410 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg003_S186_L001_R2_001.fastq## Encountered 21400 unique sequences from 31643 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg004_S187_L001_R2_001.fastq## Encountered 17754 unique sequences from 21133 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg005_S188_L001_R2_001.fastq## Encountered 13224 unique sequences from 18459 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg006_S189_L001_R2_001.fastq## Encountered 24845 unique sequences from 30218 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg007_S190_L001_R2_001.fastq## Encountered 12445 unique sequences from 14612 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg008_S191_L001_R2_001.fastq## Encountered 8847 unique sequences from 12218 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg009_S192_L001_R2_001.fastq## Encountered 15726 unique sequences from 21107 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg010_S193_L001_R2_001.fastq## Encountered 22838 unique sequences from 35028 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg011_S194_L001_R2_001.fastq## Encountered 17841 unique sequences from 25569 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg012_S195_L001_R2_001.fastq## Encountered 21094 unique sequences from 32557 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg013_S196_L001_R2_001.fastq## Encountered 10647 unique sequences from 11893 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg014_S197_L001_R2_001.fastq## Encountered 20211 unique sequences from 23693 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg015_S198_L001_R2_001.fastq## Encountered 12558 unique sequences from 17641 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg016_S199_L001_R2_001.fastq## Encountered 9333 unique sequences from 15525 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg017_S200_L001_R2_001.fastq## Encountered 8808 unique sequences from 12481 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg018_S201_L001_R2_001.fastq## Encountered 12539 unique sequences from 18766 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bg019_S202_L001_R2_001.fastq## Encountered 11658 unique sequences from 16055 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi001_S203_L001_R2_001.fastq## Encountered 12252 unique sequences from 17384 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi002_S204_L001_R2_001.fastq## Encountered 13277 unique sequences from 19912 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi003_S205_L001_R2_001.fastq## Encountered 9690 unique sequences from 12910 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi004_S206_L001_R2_001.fastq## Encountered 24844 unique sequences from 42207 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi005_S207_L001_R2_001.fastq## Encountered 91 unique sequences from 111 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi006_S208_L001_R2_001.fastq## Encountered 23958 unique sequences from 38312 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-Bi007_S209_L001_R2_001.fastq## Encountered 20075 unique sequences from 30085 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-CKC0001_S210_L001_R2_001.fastq## Encountered 7973 unique sequences from 9923 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ESE0004_S211_L001_R2_001.fastq## Encountered 10449 unique sequences from 11887 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20230909_S212_L001_R2_001.fastq## Encountered 26 unique sequences from 33 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20230923_S213_L001_R2_001.fastq## Encountered 1 unique sequences from 1 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20230924_S214_L001_R2_001.fastq## Encountered 5 unique sequences from 5 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20231007_S215_L001_R2_001.fastq## Encountered 3 unique sequences from 3 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20231008_S216_L001_R2_001.fastq## Encountered 44 unique sequences from 50 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-20231009_S217_L001_R2_001.fastq## Encountered 269 unique sequences from 358 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024220A_S218_L001_R2_001.fastq## Encountered 125 unique sequences from 131 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024220B_S219_L001_R2_001.fastq## Encountered 128 unique sequences from 129 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024221A_S220_L001_R2_001.fastq## Encountered 145 unique sequences from 159 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024221B_S221_L001_R2_001.fastq## Encountered 121 unique sequences from 130 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024222A_S222_L001_R2_001.fastq## Encountered 86 unique sequences from 88 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024222B_S223_L001_R2_001.fastq## Encountered 59 unique sequences from 76 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024312A_S224_L001_R2_001.fastq## Encountered 90 unique sequences from 104 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024312B_S225_L001_R2_001.fastq## Encountered 28 unique sequences from 28 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024314A_S226_L001_R2_001.fastq## Encountered 1 unique sequences from 1 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024319_S228_L001_R2_001.fastq## Encountered 6 unique sequences from 6 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-ext-neg-ctrl-2024320_S229_L001_R2_001.fastq## Encountered 21 unique sequences from 21 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0007_S230_L001_R2_001.fastq## Encountered 4301 unique sequences from 4798 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0027_S232_L001_R2_001.fastq## Encountered 5132 unique sequences from 5767 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0044_S233_L001_R2_001.fastq## Encountered 7465 unique sequences from 8955 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0045_S234_L001_R2_001.fastq## Encountered 5338 unique sequences from 6222 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0052_S235_L001_R2_001.fastq## Encountered 5040 unique sequences from 5529 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0054_S236_L001_R2_001.fastq## Encountered 12714 unique sequences from 16389 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0055_S237_L001_R2_001.fastq## Encountered 11946 unique sequences from 15797 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0071_S238_L001_R2_001.fastq## Encountered 9645 unique sequences from 11709 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0095_S239_L001_R2_001.fastq## Encountered 7498 unique sequences from 8701 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0096_S240_L001_R2_001.fastq## Encountered 9745 unique sequences from 14500 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0105_S241_L001_R2_001.fastq## Encountered 12394 unique sequences from 19463 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0106_S242_L001_R2_001.fastq## Encountered 4264 unique sequences from 5682 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0119_S243_L001_R2_001.fastq## Encountered 10207 unique sequences from 12665 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0134_S244_L001_R2_001.fastq## Encountered 9902 unique sequences from 11447 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0135_S245_L001_R2_001.fastq## Encountered 7059 unique sequences from 8081 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0136_S246_L001_R2_001.fastq## Encountered 2327 unique sequences from 2509 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0137_S247_L001_R2_001.fastq## Encountered 3709 unique sequences from 4076 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0138_S248_L001_R2_001.fastq## Encountered 5876 unique sequences from 6754 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0139_S249_L001_R2_001.fastq## Encountered 8067 unique sequences from 10020 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0150_S250_L001_R2_001.fastq## Encountered 11523 unique sequences from 18611 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0153_S251_L001_R2_001.fastq## Encountered 3556 unique sequences from 4536 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0155_S252_L001_R2_001.fastq## Encountered 13498 unique sequences from 17599 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0156_S253_L001_R2_001.fastq## Encountered 10678 unique sequences from 12671 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0159_S254_L001_R2_001.fastq## Encountered 6936 unique sequences from 9988 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0163_S255_L001_R2_001.fastq## Encountered 7361 unique sequences from 9958 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0165_S256_L001_R2_001.fastq## Encountered 8797 unique sequences from 12110 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0167_S257_L001_R2_001.fastq## Encountered 6907 unique sequences from 9019 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0168_S258_L001_R2_001.fastq## Encountered 5774 unique sequences from 7722 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0169_S259_L001_R2_001.fastq## Encountered 7066 unique sequences from 8051 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0170_S260_L001_R2_001.fastq## Encountered 8283 unique sequences from 9209 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0200_S261_L001_R2_001.fastq## Encountered 7229 unique sequences from 8381 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0201_S262_L001_R2_001.fastq## Encountered 20095 unique sequences from 26461 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0205_S263_L001_R2_001.fastq## Encountered 7010 unique sequences from 8493 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0209_S264_L001_R2_001.fastq## Encountered 11058 unique sequences from 14812 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0221_S265_L001_R2_001.fastq## Encountered 12556 unique sequences from 20667 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0224_S266_L001_R2_001.fastq## Encountered 4743 unique sequences from 5175 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0225_S267_L001_R2_001.fastq## Encountered 9339 unique sequences from 11502 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0227_S268_L001_R2_001.fastq## Encountered 9988 unique sequences from 11615 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0241_S269_L001_R2_001.fastq## Encountered 7863 unique sequences from 10364 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0244_S270_L001_R2_001.fastq## Encountered 2637 unique sequences from 2924 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0246_S271_L001_R2_001.fastq## Encountered 4251 unique sequences from 4743 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0248_S272_L001_R2_001.fastq## Encountered 8025 unique sequences from 9660 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0253_S273_L001_R2_001.fastq## Encountered 5779 unique sequences from 6275 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0254_S274_L001_R2_001.fastq## Encountered 15009 unique sequences from 22985 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0256_S231_L001_R2_001.fastq## Encountered 5578 unique sequences from 7938 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0259_S275_L001_R2_001.fastq## Encountered 16271 unique sequences from 19483 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0263_S276_L001_R2_001.fastq## Encountered 9682 unique sequences from 11532 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-KLS0272_S278_L001_R2_001.fastq## Encountered 8832 unique sequences from 12275 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20231021-20231119_S279_L001_R2_001.fastq## Encountered 7 unique sequences from 7 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20231022-20231120_S280_L001_R2_001.fastq## Encountered 1 unique sequences from 1 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20231023_S281_L001_R2_001.fastq## Encountered 12 unique sequences from 12 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240411_S282_L001_R2_001.fastq## Encountered 5 unique sequences from 5 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240417_S284_L001_R2_001.fastq## Encountered 252 unique sequences from 260 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240418A_S285_L001_R2_001.fastq## Encountered 261 unique sequences from 309 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240418B_S286_L001_R2_001.fastq## Encountered 50 unique sequences from 61 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240517_S287_L001_R2_001.fastq## Encountered 33 unique sequences from 33 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-20240524_S288_L001_R2_001.fastq## Encountered 2 unique sequences from 2 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-pcr-its2-neg-ctrl-Saskia-20240411_S289_L001_R2_001.fastq## Encountered 2 unique sequences from 2 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-SCA0009_S290_L001_R2_001.fastq## Encountered 10987 unique sequences from 12498 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-SCA0010_S291_L001_R2_001.fastq## Encountered 11855 unique sequences from 13374 total sequences read.## Dereplicating sequence entries in Fastq file: /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered/ITS2-SCA0013_S292_L001_R2_001.fastq## Encountered 6161 unique sequences from 6844 total sequences read.#Note that the dereplicated sequences only exist in the R environment, and are not saved into a separate output subdirectoryUpdating sample names (after samples drop out)
Extract sample names from filtF (to only include samples that passed the previous filter)
# my file names have 'junk' at the beginning and end of the file name
basename(filtFs[241])## [1] "ITS2-KLS0272_S278_L001_R1_001.fastq" strsplit(basename(filtFs[241]),"_S")## [[1]]
## [1] "ITS2-KLS0272" "278_L001_R1_001.fastq" strsplit(basename(filtFs[241]),"_S")[[1]][1]## [1] "ITS2-KLS0272"strsplit(strsplit(basename(filtFs[241]),"_S")[[1]][1],"-")[[1]]## [1] "ITS2" "KLS0272"# and their structure (esp length) differs between worker samples, queen samples, extraction negative controls, and pcr negative controls.
paste(strsplit(strsplit(basename(filtFs[241]),"_S")[[1]][1],"-")[[1]][-1],collapse="_")## [1] "KLS0272"paste(strsplit(strsplit(basename(filtFs[226]),"_S")[[1]][1],"-")[[1]][-1],collapse="_")## [1] "KLS0205"paste(strsplit(strsplit(basename(filtFs[176]),"_S")[[1]][1],"-")[[1]][-1],collapse="_")## [1] "ESE0004"paste(strsplit(strsplit(basename(filtFs[1]), "_S")[[1]][1],"-")[[1]][-1],collapse="_")## [1] "2020_6_16_H1"# make a simple function to replicate above
get.sample.name <- function(fname) paste(strsplit(strsplit(basename(fname[1]), "_S")[[1]][1],"-")[[1]][-1],collapse="_")
sample.names <- unname(sapply(filtFs, get.sample.name))
head(sample.names)## [1] "2020_6_16_H1" "2020_6_16_H5" "2020_6_16_H6" "2020_6_17_H2" "2020_6_17_H4"
## [6] "2020_6_17_H8"length(sample.names)## [1] 254# Name the dereplicated class objects by the sample names
names(derepFs) <- sample.names
names(derepRs) <- sample.names##Denoise reads to resolve exact sequences with dada2
At this step, the core sample inference algorithm is applied to the dereplicated sequences from /scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/ITS2/cutadapt/filtered (remember that the dereplicated sequences only exist in the R environment)
DADA2 infers sample sequences exactly and resolves differences of as little as 1 nucleotide using the models of the error rates we learned in the previous step
dadaFs <- dada(derepFs, err = errF, multithread = TRUE)## Sample 1 - 2 reads in 2 unique sequences.
## Sample 2 - 3 reads in 3 unique sequences.
## Sample 3 - 1 reads in 1 unique sequences.
## Sample 4 - 7 reads in 7 unique sequences.
## Sample 5 - 8 reads in 8 unique sequences.
## Sample 6 - 5 reads in 5 unique sequences.
## Sample 7 - 28544 reads in 6411 unique sequences.
## Sample 8 - 14114 reads in 3101 unique sequences.
## Sample 9 - 9775 reads in 2768 unique sequences.
## Sample 10 - 17562 reads in 4015 unique sequences.
## Sample 11 - 17183 reads in 3747 unique sequences.
## Sample 12 - 9113 reads in 2460 unique sequences.
## Sample 13 - 11400 reads in 3335 unique sequences.
## Sample 14 - 1 reads in 1 unique sequences.
## Sample 15 - 3807 reads in 1627 unique sequences.
## Sample 16 - 7207 reads in 2493 unique sequences.
## Sample 17 - 20412 reads in 4403 unique sequences.
## Sample 18 - 13330 reads in 3161 unique sequences.
## Sample 19 - 13763 reads in 3277 unique sequences.
## Sample 20 - 2 reads in 2 unique sequences.
## Sample 21 - 1 reads in 1 unique sequences.
## Sample 22 - 3 reads in 3 unique sequences.
## Sample 23 - 59663 reads in 8478 unique sequences.
## Sample 24 - 54 reads in 24 unique sequences.
## Sample 25 - 25171 reads in 6274 unique sequences.
## Sample 26 - 25820 reads in 5803 unique sequences.
## Sample 27 - 4 reads in 4 unique sequences.
## Sample 28 - 3 reads in 3 unique sequences.
## Sample 29 - 4 reads in 4 unique sequences.
## Sample 30 - 2 reads in 2 unique sequences.
## Sample 31 - 19284 reads in 5547 unique sequences.
## Sample 32 - 14455 reads in 4022 unique sequences.
## Sample 33 - 7696 reads in 2140 unique sequences.
## Sample 34 - 33662 reads in 5141 unique sequences.
## Sample 35 - 19584 reads in 4338 unique sequences.
## Sample 36 - 30473 reads in 5338 unique sequences.
## Sample 37 - 21451 reads in 4070 unique sequences.
## Sample 38 - 27667 reads in 4454 unique sequences.
## Sample 39 - 29183 reads in 5768 unique sequences.
## Sample 40 - 22468 reads in 4572 unique sequences.
## Sample 41 - 15386 reads in 2949 unique sequences.
## Sample 42 - 22706 reads in 4394 unique sequences.
## Sample 43 - 13598 reads in 3341 unique sequences.
## Sample 44 - 16586 reads in 2965 unique sequences.
## Sample 45 - 11031 reads in 2829 unique sequences.
## Sample 46 - 37109 reads in 6110 unique sequences.
## Sample 47 - 18011 reads in 4087 unique sequences.
## Sample 48 - 24520 reads in 7181 unique sequences.
## Sample 49 - 20380 reads in 4809 unique sequences.
## Sample 50 - 15119 reads in 3259 unique sequences.
## Sample 51 - 23804 reads in 4177 unique sequences.
## Sample 52 - 7846 reads in 2410 unique sequences.
## Sample 53 - 32343 reads in 5726 unique sequences.
## Sample 54 - 4382 reads in 1388 unique sequences.
## Sample 55 - 8700 reads in 2268 unique sequences.
## Sample 56 - 6167 reads in 1757 unique sequences.
## Sample 57 - 30751 reads in 6992 unique sequences.
## Sample 58 - 9885 reads in 2556 unique sequences.
## Sample 59 - 27479 reads in 5879 unique sequences.
## Sample 60 - 10700 reads in 2630 unique sequences.
## Sample 61 - 17609 reads in 2867 unique sequences.
## Sample 62 - 12038 reads in 3138 unique sequences.
## Sample 63 - 16172 reads in 3041 unique sequences.
## Sample 64 - 6 reads in 6 unique sequences.
## Sample 65 - 2 reads in 2 unique sequences.
## Sample 66 - 23260 reads in 6533 unique sequences.
## Sample 67 - 1 reads in 1 unique sequences.
## Sample 68 - 12438 reads in 3537 unique sequences.
## Sample 69 - 23534 reads in 3627 unique sequences.
## Sample 70 - 23041 reads in 4064 unique sequences.
## Sample 71 - 12263 reads in 2883 unique sequences.
## Sample 72 - 24829 reads in 4865 unique sequences.
## Sample 73 - 6086 reads in 1895 unique sequences.
## Sample 74 - 13625 reads in 2828 unique sequences.
## Sample 75 - 15490 reads in 3772 unique sequences.
## Sample 76 - 19503 reads in 3407 unique sequences.
## Sample 77 - 20699 reads in 3942 unique sequences.
## Sample 78 - 33188 reads in 6335 unique sequences.
## Sample 79 - 37485 reads in 6508 unique sequences.
## Sample 80 - 15022 reads in 3705 unique sequences.
## Sample 81 - 34675 reads in 7751 unique sequences.
## Sample 82 - 17439 reads in 4903 unique sequences.
## Sample 83 - 31265 reads in 7986 unique sequences.
## Sample 84 - 31537 reads in 6969 unique sequences.
## Sample 85 - 8136 reads in 3225 unique sequences.
## Sample 86 - 24821 reads in 5999 unique sequences.
## Sample 87 - 10606 reads in 2902 unique sequences.
## Sample 88 - 16479 reads in 4567 unique sequences.
## Sample 89 - 21254 reads in 5088 unique sequences.
## Sample 90 - 16527 reads in 3050 unique sequences.
## Sample 91 - 38333 reads in 5349 unique sequences.
## Sample 92 - 14590 reads in 3228 unique sequences.
## Sample 93 - 22545 reads in 4381 unique sequences.
## Sample 94 - 23983 reads in 5373 unique sequences.
## Sample 95 - 29295 reads in 5533 unique sequences.
## Sample 96 - 14894 reads in 3654 unique sequences.
## Sample 97 - 21650 reads in 5279 unique sequences.
## Sample 98 - 12527 reads in 2367 unique sequences.
## Sample 99 - 25406 reads in 5393 unique sequences.
## Sample 100 - 40098 reads in 7171 unique sequences.
## Sample 101 - 27389 reads in 5008 unique sequences.
## Sample 102 - 42773 reads in 7051 unique sequences.
## Sample 103 - 18663 reads in 3099 unique sequences.
## Sample 104 - 24683 reads in 3874 unique sequences.
## Sample 105 - 16886 reads in 2963 unique sequences.
## Sample 106 - 23320 reads in 3889 unique sequences.
## Sample 107 - 25858 reads in 4410 unique sequences.
## Sample 108 - 37973 reads in 6979 unique sequences.
## Sample 109 - 14762 reads in 2995 unique sequences.
## Sample 110 - 16132 reads in 2382 unique sequences.
## Sample 111 - 24378 reads in 4194 unique sequences.
## Sample 112 - 23680 reads in 3737 unique sequences.
## Sample 113 - 34917 reads in 7584 unique sequences.
## Sample 114 - 15791 reads in 3819 unique sequences.
## Sample 115 - 19770 reads in 5292 unique sequences.
## Sample 116 - 17643 reads in 4401 unique sequences.
## Sample 117 - 14039 reads in 4314 unique sequences.
## Sample 118 - 10777 reads in 3129 unique sequences.
## Sample 119 - 5537 reads in 1886 unique sequences.
## Sample 120 - 9074 reads in 3998 unique sequences.
## Sample 121 - 6275 reads in 1888 unique sequences.
## Sample 122 - 7357 reads in 2159 unique sequences.
## Sample 123 - 11309 reads in 3197 unique sequences.
## Sample 124 - 10220 reads in 3109 unique sequences.
## Sample 125 - 5421 reads in 1556 unique sequences.
## Sample 126 - 1227 reads in 309 unique sequences.
## Sample 127 - 3419 reads in 884 unique sequences.
## Sample 128 - 2193 reads in 585 unique sequences.
## Sample 129 - 8989 reads in 3182 unique sequences.
## Sample 130 - 5075 reads in 1819 unique sequences.
## Sample 131 - 15928 reads in 3718 unique sequences.
## Sample 132 - 6123 reads in 2077 unique sequences.
## Sample 133 - 3127 reads in 1087 unique sequences.
## Sample 134 - 3045 reads in 1103 unique sequences.
## Sample 135 - 318 reads in 124 unique sequences.
## Sample 136 - 2279 reads in 742 unique sequences.
## Sample 137 - 5380 reads in 2031 unique sequences.
## Sample 138 - 8859 reads in 2438 unique sequences.
## Sample 139 - 6218 reads in 1302 unique sequences.
## Sample 140 - 13981 reads in 4100 unique sequences.
## Sample 141 - 24593 reads in 5105 unique sequences.
## Sample 142 - 24923 reads in 4617 unique sequences.
## Sample 143 - 36400 reads in 5541 unique sequences.
## Sample 144 - 16550 reads in 3804 unique sequences.
## Sample 145 - 22204 reads in 3964 unique sequences.
## Sample 146 - 18314 reads in 3447 unique sequences.
## Sample 147 - 28486 reads in 4327 unique sequences.
## Sample 148 - 20792 reads in 4943 unique sequences.
## Sample 149 - 19460 reads in 5227 unique sequences.
## Sample 150 - 14410 reads in 4239 unique sequences.
## Sample 151 - 31643 reads in 7289 unique sequences.
## Sample 152 - 21133 reads in 6501 unique sequences.
## Sample 153 - 18459 reads in 4026 unique sequences.
## Sample 154 - 30218 reads in 7585 unique sequences.
## Sample 155 - 14612 reads in 3071 unique sequences.
## Sample 156 - 12218 reads in 3225 unique sequences.
## Sample 157 - 21107 reads in 5073 unique sequences.
## Sample 158 - 35028 reads in 7453 unique sequences.
## Sample 159 - 25569 reads in 5894 unique sequences.
## Sample 160 - 32557 reads in 6000 unique sequences.
## Sample 161 - 11893 reads in 2861 unique sequences.
## Sample 162 - 23693 reads in 3897 unique sequences.
## Sample 163 - 17641 reads in 3853 unique sequences.
## Sample 164 - 15525 reads in 2884 unique sequences.
## Sample 165 - 12481 reads in 3301 unique sequences.
## Sample 166 - 18766 reads in 4173 unique sequences.
## Sample 167 - 16055 reads in 3954 unique sequences.
## Sample 168 - 17384 reads in 4028 unique sequences.
## Sample 169 - 19912 reads in 4085 unique sequences.
## Sample 170 - 12910 reads in 2940 unique sequences.
## Sample 171 - 42207 reads in 6901 unique sequences.
## Sample 172 - 111 reads in 42 unique sequences.
## Sample 173 - 38312 reads in 7463 unique sequences.
## Sample 174 - 30085 reads in 6608 unique sequences.
## Sample 175 - 9923 reads in 1793 unique sequences.
## Sample 176 - 11887 reads in 3591 unique sequences.
## Sample 177 - 33 reads in 18 unique sequences.
## Sample 178 - 1 reads in 1 unique sequences.
## Sample 179 - 5 reads in 5 unique sequences.
## Sample 180 - 3 reads in 3 unique sequences.
## Sample 181 - 50 reads in 11 unique sequences.
## Sample 182 - 358 reads in 89 unique sequences.
## Sample 183 - 131 reads in 59 unique sequences.
## Sample 184 - 129 reads in 50 unique sequences.
## Sample 185 - 159 reads in 60 unique sequences.
## Sample 186 - 130 reads in 57 unique sequences.
## Sample 187 - 88 reads in 56 unique sequences.
## Sample 188 - 76 reads in 16 unique sequences.
## Sample 189 - 104 reads in 42 unique sequences.
## Sample 190 - 28 reads in 14 unique sequences.
## Sample 191 - 1 reads in 1 unique sequences.
## Sample 192 - 6 reads in 6 unique sequences.
## Sample 193 - 21 reads in 14 unique sequences.
## Sample 194 - 4798 reads in 1549 unique sequences.
## Sample 195 - 5767 reads in 1367 unique sequences.
## Sample 196 - 8955 reads in 2375 unique sequences.
## Sample 197 - 6222 reads in 1735 unique sequences.
## Sample 198 - 5529 reads in 1671 unique sequences.
## Sample 199 - 16389 reads in 2838 unique sequences.
## Sample 200 - 15797 reads in 2381 unique sequences.
## Sample 201 - 11709 reads in 3053 unique sequences.
## Sample 202 - 8701 reads in 1744 unique sequences.
## Sample 203 - 14500 reads in 3288 unique sequences.
## Sample 204 - 19463 reads in 2875 unique sequences.
## Sample 205 - 5682 reads in 1697 unique sequences.
## Sample 206 - 12665 reads in 3772 unique sequences.
## Sample 207 - 11447 reads in 2561 unique sequences.
## Sample 208 - 8081 reads in 2014 unique sequences.
## Sample 209 - 2509 reads in 874 unique sequences.
## Sample 210 - 4076 reads in 1570 unique sequences.
## Sample 211 - 6754 reads in 1459 unique sequences.
## Sample 212 - 10020 reads in 2528 unique sequences.
## Sample 213 - 18611 reads in 3695 unique sequences.
## Sample 214 - 4536 reads in 1396 unique sequences.
## Sample 215 - 17599 reads in 3534 unique sequences.
## Sample 216 - 12671 reads in 2899 unique sequences.
## Sample 217 - 9988 reads in 2257 unique sequences.
## Sample 218 - 9958 reads in 2567 unique sequences.
## Sample 219 - 12110 reads in 3012 unique sequences.
## Sample 220 - 9019 reads in 2650 unique sequences.
## Sample 221 - 7722 reads in 1809 unique sequences.
## Sample 222 - 8051 reads in 2530 unique sequences.
## Sample 223 - 9209 reads in 2997 unique sequences.
## Sample 224 - 8381 reads in 1628 unique sequences.
## Sample 225 - 26461 reads in 7103 unique sequences.
## Sample 226 - 8493 reads in 2735 unique sequences.
## Sample 227 - 14812 reads in 3356 unique sequences.
## Sample 228 - 20667 reads in 4243 unique sequences.
## Sample 229 - 5175 reads in 1922 unique sequences.
## Sample 230 - 11502 reads in 2717 unique sequences.
## Sample 231 - 11615 reads in 2383 unique sequences.
## Sample 232 - 10364 reads in 1827 unique sequences.
## Sample 233 - 2924 reads in 1098 unique sequences.
## Sample 234 - 4743 reads in 1639 unique sequences.
## Sample 235 - 9660 reads in 1900 unique sequences.
## Sample 236 - 6275 reads in 1963 unique sequences.
## Sample 237 - 22985 reads in 4974 unique sequences.
## Sample 238 - 7938 reads in 2012 unique sequences.
## Sample 239 - 19483 reads in 3905 unique sequences.
## Sample 240 - 11532 reads in 2845 unique sequences.
## Sample 241 - 12275 reads in 3381 unique sequences.
## Sample 242 - 7 reads in 7 unique sequences.
## Sample 243 - 1 reads in 1 unique sequences.
## Sample 244 - 12 reads in 8 unique sequences.
## Sample 245 - 5 reads in 5 unique sequences.
## Sample 246 - 260 reads in 110 unique sequences.
## Sample 247 - 309 reads in 103 unique sequences.
## Sample 248 - 61 reads in 32 unique sequences.
## Sample 249 - 33 reads in 10 unique sequences.
## Sample 250 - 2 reads in 1 unique sequences.
## Sample 251 - 2 reads in 2 unique sequences.
## Sample 252 - 12498 reads in 3854 unique sequences.
## Sample 253 - 13374 reads in 3950 unique sequences.
## Sample 254 - 6844 reads in 2230 unique sequences.dadaRs <- dada(derepRs, err = errR, multithread = TRUE)## Sample 1 - 2 reads in 2 unique sequences.
## Sample 2 - 3 reads in 3 unique sequences.
## Sample 3 - 1 reads in 1 unique sequences.
## Sample 4 - 7 reads in 7 unique sequences.
## Sample 5 - 8 reads in 8 unique sequences.
## Sample 6 - 5 reads in 5 unique sequences.
## Sample 7 - 28544 reads in 20651 unique sequences.
## Sample 8 - 14114 reads in 9292 unique sequences.
## Sample 9 - 9775 reads in 8987 unique sequences.
## Sample 10 - 17562 reads in 12234 unique sequences.
## Sample 11 - 17183 reads in 12653 unique sequences.
## Sample 12 - 9113 reads in 7680 unique sequences.
## Sample 13 - 11400 reads in 8576 unique sequences.
## Sample 14 - 1 reads in 1 unique sequences.
## Sample 15 - 3807 reads in 3775 unique sequences.
## Sample 16 - 7207 reads in 6335 unique sequences.
## Sample 17 - 20412 reads in 14856 unique sequences.
## Sample 18 - 13330 reads in 9488 unique sequences.
## Sample 19 - 13763 reads in 9633 unique sequences.
## Sample 20 - 2 reads in 2 unique sequences.
## Sample 21 - 1 reads in 1 unique sequences.
## Sample 22 - 3 reads in 3 unique sequences.
## Sample 23 - 59663 reads in 37458 unique sequences.
## Sample 24 - 54 reads in 52 unique sequences.
## Sample 25 - 25171 reads in 21493 unique sequences.
## Sample 26 - 25820 reads in 18015 unique sequences.
## Sample 27 - 4 reads in 4 unique sequences.
## Sample 28 - 3 reads in 3 unique sequences.
## Sample 29 - 4 reads in 4 unique sequences.
## Sample 30 - 2 reads in 2 unique sequences.
## Sample 31 - 19284 reads in 13885 unique sequences.
## Sample 32 - 14455 reads in 11100 unique sequences.
## Sample 33 - 7696 reads in 5723 unique sequences.
## Sample 34 - 33662 reads in 18255 unique sequences.
## Sample 35 - 19584 reads in 13414 unique sequences.
## Sample 36 - 30473 reads in 17392 unique sequences.
## Sample 37 - 21451 reads in 15131 unique sequences.
## Sample 38 - 27667 reads in 15157 unique sequences.
## Sample 39 - 29183 reads in 18315 unique sequences.
## Sample 40 - 22468 reads in 16215 unique sequences.
## Sample 41 - 15386 reads in 9976 unique sequences.
## Sample 42 - 22706 reads in 16545 unique sequences.
## Sample 43 - 13598 reads in 10501 unique sequences.
## Sample 44 - 16586 reads in 9094 unique sequences.
## Sample 45 - 11031 reads in 8284 unique sequences.
## Sample 46 - 37109 reads in 23005 unique sequences.
## Sample 47 - 18011 reads in 14602 unique sequences.
## Sample 48 - 24520 reads in 19816 unique sequences.
## Sample 49 - 20380 reads in 14096 unique sequences.
## Sample 50 - 15119 reads in 10484 unique sequences.
## Sample 51 - 23804 reads in 14554 unique sequences.
## Sample 52 - 7846 reads in 7481 unique sequences.
## Sample 53 - 32343 reads in 25806 unique sequences.
## Sample 54 - 4382 reads in 4201 unique sequences.
## Sample 55 - 8700 reads in 7890 unique sequences.
## Sample 56 - 6167 reads in 5707 unique sequences.
## Sample 57 - 30751 reads in 21761 unique sequences.
## Sample 58 - 9885 reads in 8981 unique sequences.
## Sample 59 - 27479 reads in 20131 unique sequences.
## Sample 60 - 10700 reads in 10106 unique sequences.
## Sample 61 - 17609 reads in 12430 unique sequences.
## Sample 62 - 12038 reads in 10588 unique sequences.
## Sample 63 - 16172 reads in 9763 unique sequences.
## Sample 64 - 6 reads in 6 unique sequences.
## Sample 65 - 2 reads in 2 unique sequences.
## Sample 66 - 23260 reads in 16302 unique sequences.
## Sample 67 - 1 reads in 1 unique sequences.
## Sample 68 - 12438 reads in 9380 unique sequences.
## Sample 69 - 23534 reads in 12352 unique sequences.
## Sample 70 - 23041 reads in 13309 unique sequences.
## Sample 71 - 12263 reads in 8624 unique sequences.
## Sample 72 - 24829 reads in 17396 unique sequences.
## Sample 73 - 6086 reads in 5638 unique sequences.
## Sample 74 - 13625 reads in 9379 unique sequences.
## Sample 75 - 15490 reads in 11650 unique sequences.
## Sample 76 - 19503 reads in 12010 unique sequences.
## Sample 77 - 20699 reads in 13041 unique sequences.
## Sample 78 - 33188 reads in 21643 unique sequences.
## Sample 79 - 37485 reads in 22444 unique sequences.
## Sample 80 - 15022 reads in 13802 unique sequences.
## Sample 81 - 34675 reads in 26469 unique sequences.
## Sample 82 - 17439 reads in 13441 unique sequences.
## Sample 83 - 31265 reads in 23138 unique sequences.
## Sample 84 - 31537 reads in 22363 unique sequences.
## Sample 85 - 8136 reads in 6823 unique sequences.
## Sample 86 - 24821 reads in 18833 unique sequences.
## Sample 87 - 10606 reads in 7990 unique sequences.
## Sample 88 - 16479 reads in 12619 unique sequences.
## Sample 89 - 21254 reads in 14780 unique sequences.
## Sample 90 - 16527 reads in 9264 unique sequences.
## Sample 91 - 38333 reads in 23279 unique sequences.
## Sample 92 - 14590 reads in 10008 unique sequences.
## Sample 93 - 22545 reads in 14492 unique sequences.
## Sample 94 - 23983 reads in 19089 unique sequences.
## Sample 95 - 29295 reads in 24471 unique sequences.
## Sample 96 - 14894 reads in 12485 unique sequences.
## Sample 97 - 21650 reads in 15401 unique sequences.
## Sample 98 - 12527 reads in 10946 unique sequences.
## Sample 99 - 25406 reads in 18471 unique sequences.
## Sample 100 - 40098 reads in 23929 unique sequences.
## Sample 101 - 27389 reads in 17741 unique sequences.
## Sample 102 - 42773 reads in 30297 unique sequences.
## Sample 103 - 18663 reads in 10825 unique sequences.
## Sample 104 - 24683 reads in 16829 unique sequences.
## Sample 105 - 16886 reads in 12554 unique sequences.
## Sample 106 - 23320 reads in 16740 unique sequences.
## Sample 107 - 25858 reads in 18169 unique sequences.
## Sample 108 - 37973 reads in 24915 unique sequences.
## Sample 109 - 14762 reads in 10851 unique sequences.
## Sample 110 - 16132 reads in 13001 unique sequences.
## Sample 111 - 24378 reads in 18245 unique sequences.
## Sample 112 - 23680 reads in 14175 unique sequences.
## Sample 113 - 34917 reads in 25007 unique sequences.
## Sample 114 - 15791 reads in 12933 unique sequences.
## Sample 115 - 19770 reads in 15802 unique sequences.
## Sample 116 - 17643 reads in 12828 unique sequences.
## Sample 117 - 14039 reads in 10897 unique sequences.
## Sample 118 - 10777 reads in 9564 unique sequences.
## Sample 119 - 5537 reads in 4555 unique sequences.
## Sample 120 - 9074 reads in 8468 unique sequences.
## Sample 121 - 6275 reads in 5272 unique sequences.
## Sample 122 - 7357 reads in 6020 unique sequences.
## Sample 123 - 11309 reads in 9127 unique sequences.
## Sample 124 - 10220 reads in 8578 unique sequences.
## Sample 125 - 5421 reads in 4481 unique sequences.
## Sample 126 - 1227 reads in 896 unique sequences.
## Sample 127 - 3419 reads in 2604 unique sequences.
## Sample 128 - 2193 reads in 1601 unique sequences.
## Sample 129 - 8989 reads in 8187 unique sequences.
## Sample 130 - 5075 reads in 4100 unique sequences.
## Sample 131 - 15928 reads in 11477 unique sequences.
## Sample 132 - 6123 reads in 5391 unique sequences.
## Sample 133 - 3127 reads in 2729 unique sequences.
## Sample 134 - 3045 reads in 2477 unique sequences.
## Sample 135 - 318 reads in 291 unique sequences.
## Sample 136 - 2279 reads in 1751 unique sequences.
## Sample 137 - 5380 reads in 4355 unique sequences.
## Sample 138 - 8859 reads in 6953 unique sequences.
## Sample 139 - 6218 reads in 5238 unique sequences.
## Sample 140 - 13981 reads in 12357 unique sequences.
## Sample 141 - 24593 reads in 17515 unique sequences.
## Sample 142 - 24923 reads in 19635 unique sequences.
## Sample 143 - 36400 reads in 20105 unique sequences.
## Sample 144 - 16550 reads in 11672 unique sequences.
## Sample 145 - 22204 reads in 18751 unique sequences.
## Sample 146 - 18314 reads in 13171 unique sequences.
## Sample 147 - 28486 reads in 21411 unique sequences.
## Sample 148 - 20792 reads in 16159 unique sequences.
## Sample 149 - 19460 reads in 15587 unique sequences.
## Sample 150 - 14410 reads in 11341 unique sequences.
## Sample 151 - 31643 reads in 21400 unique sequences.
## Sample 152 - 21133 reads in 17754 unique sequences.
## Sample 153 - 18459 reads in 13224 unique sequences.
## Sample 154 - 30218 reads in 24845 unique sequences.
## Sample 155 - 14612 reads in 12445 unique sequences.
## Sample 156 - 12218 reads in 8847 unique sequences.
## Sample 157 - 21107 reads in 15726 unique sequences.
## Sample 158 - 35028 reads in 22838 unique sequences.
## Sample 159 - 25569 reads in 17841 unique sequences.
## Sample 160 - 32557 reads in 21094 unique sequences.
## Sample 161 - 11893 reads in 10647 unique sequences.
## Sample 162 - 23693 reads in 20211 unique sequences.
## Sample 163 - 17641 reads in 12558 unique sequences.
## Sample 164 - 15525 reads in 9333 unique sequences.
## Sample 165 - 12481 reads in 8808 unique sequences.
## Sample 166 - 18766 reads in 12539 unique sequences.
## Sample 167 - 16055 reads in 11658 unique sequences.
## Sample 168 - 17384 reads in 12252 unique sequences.
## Sample 169 - 19912 reads in 13277 unique sequences.
## Sample 170 - 12910 reads in 9690 unique sequences.
## Sample 171 - 42207 reads in 24844 unique sequences.
## Sample 172 - 111 reads in 91 unique sequences.
## Sample 173 - 38312 reads in 23958 unique sequences.
## Sample 174 - 30085 reads in 20075 unique sequences.
## Sample 175 - 9923 reads in 7973 unique sequences.
## Sample 176 - 11887 reads in 10449 unique sequences.
## Sample 177 - 33 reads in 26 unique sequences.
## Sample 178 - 1 reads in 1 unique sequences.
## Sample 179 - 5 reads in 5 unique sequences.
## Sample 180 - 3 reads in 3 unique sequences.
## Sample 181 - 50 reads in 44 unique sequences.
## Sample 182 - 358 reads in 269 unique sequences.
## Sample 183 - 131 reads in 125 unique sequences.
## Sample 184 - 129 reads in 128 unique sequences.
## Sample 185 - 159 reads in 145 unique sequences.
## Sample 186 - 130 reads in 121 unique sequences.
## Sample 187 - 88 reads in 86 unique sequences.
## Sample 188 - 76 reads in 59 unique sequences.
## Sample 189 - 104 reads in 90 unique sequences.
## Sample 190 - 28 reads in 28 unique sequences.
## Sample 191 - 1 reads in 1 unique sequences.
## Sample 192 - 6 reads in 6 unique sequences.
## Sample 193 - 21 reads in 21 unique sequences.
## Sample 194 - 4798 reads in 4301 unique sequences.
## Sample 195 - 5767 reads in 5132 unique sequences.
## Sample 196 - 8955 reads in 7465 unique sequences.
## Sample 197 - 6222 reads in 5338 unique sequences.
## Sample 198 - 5529 reads in 5040 unique sequences.
## Sample 199 - 16389 reads in 12714 unique sequences.
## Sample 200 - 15797 reads in 11946 unique sequences.
## Sample 201 - 11709 reads in 9645 unique sequences.
## Sample 202 - 8701 reads in 7498 unique sequences.
## Sample 203 - 14500 reads in 9745 unique sequences.
## Sample 204 - 19463 reads in 12394 unique sequences.
## Sample 205 - 5682 reads in 4264 unique sequences.
## Sample 206 - 12665 reads in 10207 unique sequences.
## Sample 207 - 11447 reads in 9902 unique sequences.
## Sample 208 - 8081 reads in 7059 unique sequences.
## Sample 209 - 2509 reads in 2327 unique sequences.
## Sample 210 - 4076 reads in 3709 unique sequences.
## Sample 211 - 6754 reads in 5876 unique sequences.
## Sample 212 - 10020 reads in 8067 unique sequences.
## Sample 213 - 18611 reads in 11523 unique sequences.
## Sample 214 - 4536 reads in 3556 unique sequences.
## Sample 215 - 17599 reads in 13498 unique sequences.
## Sample 216 - 12671 reads in 10678 unique sequences.
## Sample 217 - 9988 reads in 6936 unique sequences.
## Sample 218 - 9958 reads in 7361 unique sequences.
## Sample 219 - 12110 reads in 8797 unique sequences.
## Sample 220 - 9019 reads in 6907 unique sequences.
## Sample 221 - 7722 reads in 5774 unique sequences.
## Sample 222 - 8051 reads in 7066 unique sequences.
## Sample 223 - 9209 reads in 8283 unique sequences.
## Sample 224 - 8381 reads in 7229 unique sequences.
## Sample 225 - 26461 reads in 20095 unique sequences.
## Sample 226 - 8493 reads in 7010 unique sequences.
## Sample 227 - 14812 reads in 11058 unique sequences.
## Sample 228 - 20667 reads in 12556 unique sequences.
## Sample 229 - 5175 reads in 4743 unique sequences.
## Sample 230 - 11502 reads in 9339 unique sequences.
## Sample 231 - 11615 reads in 9988 unique sequences.
## Sample 232 - 10364 reads in 7863 unique sequences.
## Sample 233 - 2924 reads in 2637 unique sequences.
## Sample 234 - 4743 reads in 4251 unique sequences.
## Sample 235 - 9660 reads in 8025 unique sequences.
## Sample 236 - 6275 reads in 5779 unique sequences.
## Sample 237 - 22985 reads in 15009 unique sequences.
## Sample 238 - 7938 reads in 5578 unique sequences.
## Sample 239 - 19483 reads in 16271 unique sequences.
## Sample 240 - 11532 reads in 9682 unique sequences.
## Sample 241 - 12275 reads in 8832 unique sequences.
## Sample 242 - 7 reads in 7 unique sequences.
## Sample 243 - 1 reads in 1 unique sequences.
## Sample 244 - 12 reads in 12 unique sequences.
## Sample 245 - 5 reads in 5 unique sequences.
## Sample 246 - 260 reads in 252 unique sequences.
## Sample 247 - 309 reads in 261 unique sequences.
## Sample 248 - 61 reads in 50 unique sequences.
## Sample 249 - 33 reads in 33 unique sequences.
## Sample 250 - 2 reads in 2 unique sequences.
## Sample 251 - 2 reads in 2 unique sequences.
## Sample 252 - 12498 reads in 10987 unique sequences.
## Sample 253 - 13374 reads in 11855 unique sequences.
## Sample 254 - 6844 reads in 6161 unique sequences.Merge paired reads
We’ve inferred the sample sequences in the forward and reverse reads independently. Now it’s time to merge those inferred sequences together, throwing out those pairs of reads that don’t match
mergers <- mergePairs(dadaFs, derepFs, dadaRs, derepRs, verbose=TRUE, minOverlap = 11, maxMismatch = 0)## No paired-reads (in ZERO unique pairings) successfully merged out of 2 pairings) input.## No paired-reads (in ZERO unique pairings) successfully merged out of 3 pairings) input.## 1 paired-reads (in 1 unique pairings) successfully merged out of 1 (in 1 pairings) input.## No paired-reads (in ZERO unique pairings) successfully merged out of 7 pairings) input.## No paired-reads (in ZERO unique pairings) successfully merged out of 8 pairings) input.## 0 paired-reads (in 0 unique pairings) successfully merged out of 1 (in 1 pairings) input.## 12098 paired-reads (in 34 unique pairings) successfully merged out of 28223 (in 206 pairings) input.## 6915 paired-reads (in 10 unique pairings) successfully merged out of 13914 (in 83 pairings) input.## 6289 paired-reads (in 14 unique pairings) successfully merged out of 9549 (in 68 pairings) input.## 11248 paired-reads (in 23 unique pairings) successfully merged out of 17279 (in 108 pairings) input.## 5175 paired-reads (in 9 unique pairings) successfully merged out of 16402 (in 78 pairings) input.## 4569 paired-reads (in 8 unique pairings) successfully merged out of 8843 (in 59 pairings) input.## 7602 paired-reads (in 20 unique pairings) successfully merged out of 11094 (in 84 pairings) input.## 0 paired-reads (in 0 unique pairings) successfully merged out of 1 (in 1 pairings) input.## 523 paired-reads (in 2 unique pairings) successfully merged out of 3077 (in 28 pairings) input.## 4726 paired-reads (in 13 unique pairings) successfully merged out of 6996 (in 65 pairings) input.## 11122 paired-reads (in 26 unique pairings) successfully merged out of 19790 (in 116 pairings) input.## 9082 paired-reads (in 20 unique pairings) successfully merged out of 13139 (in 94 pairings) input.## 8180 paired-reads (in 21 unique pairings) successfully merged out of 13513 (in 103 pairings) input.## No paired-reads (in ZERO unique pairings) successfully merged out of 2 pairings) input.## 0 paired-reads (in 0 unique pairings) successfully merged out of 1 (in 1 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 1 (in 1 pairings) input.## 43369 paired-reads (in 52 unique pairings) successfully merged out of 59078 (in 369 pairings) input.## 0 paired-reads (in 0 unique pairings) successfully merged out of 12 (in 1 pairings) input.## 14971 paired-reads (in 23 unique pairings) successfully merged out of 24702 (in 144 pairings) input.## 7418 paired-reads (in 18 unique pairings) successfully merged out of 25469 (in 177 pairings) input.## 0 paired-reads (in 0 unique pairings) successfully merged out of 1 (in 1 pairings) input.## No paired-reads (in ZERO unique pairings) successfully merged out of 3 pairings) input.## No paired-reads (in ZERO unique pairings) successfully merged out of 4 pairings) input.## No paired-reads (in ZERO unique pairings) successfully merged out of 2 pairings) input.## 8781 paired-reads (in 27 unique pairings) successfully merged out of 18833 (in 174 pairings) input.## 5466 paired-reads (in 15 unique pairings) successfully merged out of 14208 (in 106 pairings) input.## 4279 paired-reads (in 12 unique pairings) successfully merged out of 7485 (in 51 pairings) input.## 15660 paired-reads (in 17 unique pairings) successfully merged out of 33211 (in 146 pairings) input.## 11578 paired-reads (in 23 unique pairings) successfully merged out of 19164 (in 156 pairings) input.## 16707 paired-reads (in 28 unique pairings) successfully merged out of 30222 (in 214 pairings) input.## 12751 paired-reads (in 22 unique pairings) successfully merged out of 20990 (in 125 pairings) input.## 15278 paired-reads (in 15 unique pairings) successfully merged out of 27419 (in 153 pairings) input.## 12859 paired-reads (in 14 unique pairings) successfully merged out of 28889 (in 183 pairings) input.## 11442 paired-reads (in 21 unique pairings) successfully merged out of 22212 (in 152 pairings) input.## 7963 paired-reads (in 11 unique pairings) successfully merged out of 14806 (in 86 pairings) input.## 9979 paired-reads (in 24 unique pairings) successfully merged out of 22382 (in 150 pairings) input.## 3102 paired-reads (in 10 unique pairings) successfully merged out of 13375 (in 109 pairings) input.## 7729 paired-reads (in 8 unique pairings) successfully merged out of 16037 (in 82 pairings) input.## 4747 paired-reads (in 10 unique pairings) successfully merged out of 10843 (in 82 pairings) input.## 21916 paired-reads (in 24 unique pairings) successfully merged out of 36924 (in 225 pairings) input.## 14493 paired-reads (in 18 unique pairings) successfully merged out of 17755 (in 103 pairings) input.## 15568 paired-reads (in 39 unique pairings) successfully merged out of 24236 (in 184 pairings) input.## 10311 paired-reads (in 27 unique pairings) successfully merged out of 20098 (in 177 pairings) input.## 6896 paired-reads (in 11 unique pairings) successfully merged out of 14883 (in 99 pairings) input.## 12637 paired-reads (in 18 unique pairings) successfully merged out of 23495 (in 137 pairings) input.## 3278 paired-reads (in 14 unique pairings) successfully merged out of 7539 (in 81 pairings) input.## 24879 paired-reads (in 46 unique pairings) successfully merged out of 31504 (in 180 pairings) input.## 2757 paired-reads (in 9 unique pairings) successfully merged out of 4258 (in 28 pairings) input.## 5251 paired-reads (in 15 unique pairings) successfully merged out of 8456 (in 76 pairings) input.## 3509 paired-reads (in 19 unique pairings) successfully merged out of 5978 (in 65 pairings) input.## 21365 paired-reads (in 47 unique pairings) successfully merged out of 30337 (in 263 pairings) input.## 6862 paired-reads (in 19 unique pairings) successfully merged out of 9275 (in 91 pairings) input.## 16440 paired-reads (in 35 unique pairings) successfully merged out of 27100 (in 227 pairings) input.## 5426 paired-reads (in 9 unique pairings) successfully merged out of 10508 (in 71 pairings) input.## 10586 paired-reads (in 11 unique pairings) successfully merged out of 17469 (in 93 pairings) input.## 6471 paired-reads (in 9 unique pairings) successfully merged out of 11850 (in 67 pairings) input.## 7762 paired-reads (in 14 unique pairings) successfully merged out of 15996 (in 132 pairings) input.## No paired-reads (in ZERO unique pairings) successfully merged out of 6 pairings) input.## No paired-reads (in ZERO unique pairings) successfully merged out of 2 pairings) input.## 13299 paired-reads (in 27 unique pairings) successfully merged out of 22660 (in 233 pairings) input.## 0 paired-reads (in 0 unique pairings) successfully merged out of 1 (in 1 pairings) input.## 8306 paired-reads (in 21 unique pairings) successfully merged out of 12156 (in 94 pairings) input.## 11417 paired-reads (in 19 unique pairings) successfully merged out of 23417 (in 151 pairings) input.## 13604 paired-reads (in 20 unique pairings) successfully merged out of 22949 (in 153 pairings) input.## 562 paired-reads (in 5 unique pairings) successfully merged out of 11782 (in 68 pairings) input.## 13128 paired-reads (in 18 unique pairings) successfully merged out of 24567 (in 191 pairings) input.## 1110 paired-reads (in 9 unique pairings) successfully merged out of 5771 (in 42 pairings) input.## 2698 paired-reads (in 6 unique pairings) successfully merged out of 13453 (in 74 pairings) input.## 2908 paired-reads (in 15 unique pairings) successfully merged out of 15311 (in 127 pairings) input.## 2064 paired-reads (in 6 unique pairings) successfully merged out of 19339 (in 89 pairings) input.## 5256 paired-reads (in 17 unique pairings) successfully merged out of 20480 (in 153 pairings) input.## 9490 paired-reads (in 25 unique pairings) successfully merged out of 32763 (in 215 pairings) input.## 7580 paired-reads (in 24 unique pairings) successfully merged out of 37205 (in 255 pairings) input.## 6672 paired-reads (in 16 unique pairings) successfully merged out of 14911 (in 108 pairings) input.## 16009 paired-reads (in 44 unique pairings) successfully merged out of 34149 (in 299 pairings) input.## 4635 paired-reads (in 20 unique pairings) successfully merged out of 16893 (in 124 pairings) input.## 9531 paired-reads (in 22 unique pairings) successfully merged out of 30611 (in 276 pairings) input.## 6982 paired-reads (in 26 unique pairings) successfully merged out of 31222 (in 256 pairings) input.## 1635 paired-reads (in 7 unique pairings) successfully merged out of 7905 (in 74 pairings) input.## 9736 paired-reads (in 27 unique pairings) successfully merged out of 24170 (in 181 pairings) input.## 5163 paired-reads (in 12 unique pairings) successfully merged out of 10444 (in 96 pairings) input.## 7162 paired-reads (in 20 unique pairings) successfully merged out of 15870 (in 132 pairings) input.## 3934 paired-reads (in 11 unique pairings) successfully merged out of 21033 (in 111 pairings) input.## 9485 paired-reads (in 12 unique pairings) successfully merged out of 16330 (in 94 pairings) input.## 2996 paired-reads (in 5 unique pairings) successfully merged out of 38118 (in 177 pairings) input.## 4780 paired-reads (in 16 unique pairings) successfully merged out of 14457 (in 89 pairings) input.## 1051 paired-reads (in 7 unique pairings) successfully merged out of 22203 (in 106 pairings) input.## 17240 paired-reads (in 31 unique pairings) successfully merged out of 23590 (in 151 pairings) input.## 22208 paired-reads (in 28 unique pairings) successfully merged out of 28900 (in 147 pairings) input.## 12309 paired-reads (in 28 unique pairings) successfully merged out of 14507 (in 118 pairings) input.## 14640 paired-reads (in 39 unique pairings) successfully merged out of 21216 (in 202 pairings) input.## 10208 paired-reads (in 14 unique pairings) successfully merged out of 12318 (in 78 pairings) input.## 15083 paired-reads (in 18 unique pairings) successfully merged out of 25217 (in 171 pairings) input.## 30515 paired-reads (in 33 unique pairings) successfully merged out of 39770 (in 194 pairings) input.## 18773 paired-reads (in 18 unique pairings) successfully merged out of 27174 (in 151 pairings) input.## 24512 paired-reads (in 29 unique pairings) successfully merged out of 42360 (in 310 pairings) input.## 13395 paired-reads (in 14 unique pairings) successfully merged out of 18513 (in 84 pairings) input.## 18901 paired-reads (in 8 unique pairings) successfully merged out of 24461 (in 115 pairings) input.## 12854 paired-reads (in 10 unique pairings) successfully merged out of 16681 (in 92 pairings) input.## 18740 paired-reads (in 19 unique pairings) successfully merged out of 23030 (in 127 pairings) input.## 19567 paired-reads (in 14 unique pairings) successfully merged out of 25416 (in 129 pairings) input.## 29072 paired-reads (in 63 unique pairings) successfully merged out of 37532 (in 298 pairings) input.## 8658 paired-reads (in 9 unique pairings) successfully merged out of 14614 (in 118 pairings) input.## 8667 paired-reads (in 10 unique pairings) successfully merged out of 15915 (in 54 pairings) input.## 16093 paired-reads (in 16 unique pairings) successfully merged out of 23861 (in 178 pairings) input.## 14789 paired-reads (in 16 unique pairings) successfully merged out of 23251 (in 148 pairings) input.## 24572 paired-reads (in 33 unique pairings) successfully merged out of 34565 (in 209 pairings) input.## 7729 paired-reads (in 25 unique pairings) successfully merged out of 15286 (in 100 pairings) input.## 12705 paired-reads (in 36 unique pairings) successfully merged out of 19303 (in 202 pairings) input.## 13904 paired-reads (in 19 unique pairings) successfully merged out of 17420 (in 100 pairings) input.## 3926 paired-reads (in 16 unique pairings) successfully merged out of 13608 (in 139 pairings) input.## 2532 paired-reads (in 3 unique pairings) successfully merged out of 10646 (in 41 pairings) input.## 669 paired-reads (in 6 unique pairings) successfully merged out of 5072 (in 40 pairings) input.## 1163 paired-reads (in 6 unique pairings) successfully merged out of 8703 (in 66 pairings) input.## 2744 paired-reads (in 7 unique pairings) successfully merged out of 6097 (in 53 pairings) input.## 3980 paired-reads (in 8 unique pairings) successfully merged out of 7151 (in 56 pairings) input.## 2775 paired-reads (in 17 unique pairings) successfully merged out of 10901 (in 159 pairings) input.## 1821 paired-reads (in 13 unique pairings) successfully merged out of 9942 (in 53 pairings) input.## 2753 paired-reads (in 13 unique pairings) successfully merged out of 5233 (in 49 pairings) input.## 805 paired-reads (in 3 unique pairings) successfully merged out of 1125 (in 10 pairings) input.## 2603 paired-reads (in 7 unique pairings) successfully merged out of 3368 (in 32 pairings) input.## 1600 paired-reads (in 6 unique pairings) successfully merged out of 2139 (in 24 pairings) input.## 3461 paired-reads (in 16 unique pairings) successfully merged out of 8496 (in 92 pairings) input.## 2232 paired-reads (in 6 unique pairings) successfully merged out of 4677 (in 35 pairings) input.## 8121 paired-reads (in 22 unique pairings) successfully merged out of 15589 (in 172 pairings) input.## 2009 paired-reads (in 11 unique pairings) successfully merged out of 5254 (in 39 pairings) input.## 1185 paired-reads (in 2 unique pairings) successfully merged out of 2962 (in 20 pairings) input.## 0 paired-reads (in 0 unique pairings) successfully merged out of 2818 (in 21 pairings) input.## 105 paired-reads (in 2 unique pairings) successfully merged out of 301 (in 5 pairings) input.## 1291 paired-reads (in 3 unique pairings) successfully merged out of 2186 (in 14 pairings) input.## 1745 paired-reads (in 5 unique pairings) successfully merged out of 5049 (in 47 pairings) input.## 6343 paired-reads (in 18 unique pairings) successfully merged out of 8478 (in 58 pairings) input.## 0 paired-reads (in 0 unique pairings) successfully merged out of 5924 (in 12 pairings) input.## 87 paired-reads (in 3 unique pairings) successfully merged out of 13222 (in 139 pairings) input.## 11416 paired-reads (in 11 unique pairings) successfully merged out of 24075 (in 124 pairings) input.## 7001 paired-reads (in 17 unique pairings) successfully merged out of 24391 (in 117 pairings) input.## 1560 paired-reads (in 10 unique pairings) successfully merged out of 36117 (in 106 pairings) input.## 6032 paired-reads (in 13 unique pairings) successfully merged out of 16252 (in 93 pairings) input.## 5252 paired-reads (in 12 unique pairings) successfully merged out of 21879 (in 91 pairings) input.## 535 paired-reads (in 7 unique pairings) successfully merged out of 18058 (in 100 pairings) input.## 117 paired-reads (in 2 unique pairings) successfully merged out of 27863 (in 77 pairings) input.## 839 paired-reads (in 8 unique pairings) successfully merged out of 20363 (in 102 pairings) input.## 5403 paired-reads (in 20 unique pairings) successfully merged out of 18958 (in 137 pairings) input.## 4965 paired-reads (in 15 unique pairings) successfully merged out of 13848 (in 118 pairings) input.## 5273 paired-reads (in 18 unique pairings) successfully merged out of 30370 (in 170 pairings) input.## 3256 paired-reads (in 22 unique pairings) successfully merged out of 20438 (in 160 pairings) input.## 2314 paired-reads (in 8 unique pairings) successfully merged out of 18143 (in 86 pairings) input.## 9699 paired-reads (in 20 unique pairings) successfully merged out of 29611 (in 231 pairings) input.## 7078 paired-reads (in 18 unique pairings) successfully merged out of 14260 (in 94 pairings) input.## 3054 paired-reads (in 7 unique pairings) successfully merged out of 11933 (in 72 pairings) input.## 10561 paired-reads (in 18 unique pairings) successfully merged out of 20790 (in 150 pairings) input.## 1418 paired-reads (in 14 unique pairings) successfully merged out of 34459 (in 213 pairings) input.## 3272 paired-reads (in 22 unique pairings) successfully merged out of 24937 (in 170 pairings) input.## 11465 paired-reads (in 16 unique pairings) successfully merged out of 32095 (in 154 pairings) input.## 153 paired-reads (in 2 unique pairings) successfully merged out of 11373 (in 56 pairings) input.## 8480 paired-reads (in 15 unique pairings) successfully merged out of 23320 (in 76 pairings) input.## 5360 paired-reads (in 8 unique pairings) successfully merged out of 17234 (in 124 pairings) input.## 11926 paired-reads (in 14 unique pairings) successfully merged out of 15245 (in 71 pairings) input.## 6243 paired-reads (in 17 unique pairings) successfully merged out of 12181 (in 98 pairings) input.## 10936 paired-reads (in 13 unique pairings) successfully merged out of 17960 (in 77 pairings) input.## 7820 paired-reads (in 12 unique pairings) successfully merged out of 15748 (in 84 pairings) input.## 7192 paired-reads (in 15 unique pairings) successfully merged out of 16965 (in 90 pairings) input.## 2960 paired-reads (in 14 unique pairings) successfully merged out of 19527 (in 118 pairings) input.## 4813 paired-reads (in 7 unique pairings) successfully merged out of 12736 (in 81 pairings) input.## 2019 paired-reads (in 13 unique pairings) successfully merged out of 41792 (in 184 pairings) input.## 0 paired-reads (in 0 unique pairings) successfully merged out of 96 (in 3 pairings) input.## 3284 paired-reads (in 18 unique pairings) successfully merged out of 37790 (in 217 pairings) input.## 18262 paired-reads (in 41 unique pairings) successfully merged out of 29409 (in 216 pairings) input.## 7687 paired-reads (in 6 unique pairings) successfully merged out of 9784 (in 34 pairings) input.## 2705 paired-reads (in 15 unique pairings) successfully merged out of 11508 (in 73 pairings) input.## 20 paired-reads (in 2 unique pairings) successfully merged out of 20 (in 2 pairings) input.## 1 paired-reads (in 1 unique pairings) successfully merged out of 1 (in 1 pairings) input.## No paired-reads (in ZERO unique pairings) successfully merged out of 5 pairings) input.## No paired-reads (in ZERO unique pairings) successfully merged out of 3 pairings) input.## 36 paired-reads (in 1 unique pairings) successfully merged out of 48 (in 2 pairings) input.## 272 paired-reads (in 2 unique pairings) successfully merged out of 332 (in 3 pairings) input.## 44 paired-reads (in 2 unique pairings) successfully merged out of 48 (in 3 pairings) input.## 0 paired-reads (in 0 unique pairings) successfully merged out of 22 (in 1 pairings) input.## 0 paired-reads (in 0 unique pairings) successfully merged out of 44 (in 1 pairings) input.## 9 paired-reads (in 1 unique pairings) successfully merged out of 74 (in 4 pairings) input.## 0 paired-reads (in 0 unique pairings) successfully merged out of 5 (in 1 pairings) input.## 54 paired-reads (in 1 unique pairings) successfully merged out of 54 (in 1 pairings) input.## 49 paired-reads (in 1 unique pairings) successfully merged out of 49 (in 1 pairings) input.## 0 paired-reads (in 0 unique pairings) successfully merged out of 4 (in 1 pairings) input.## 1 paired-reads (in 1 unique pairings) successfully merged out of 1 (in 1 pairings) input.## No paired-reads (in ZERO unique pairings) successfully merged out of 6 pairings) input.## No paired-reads (in ZERO unique pairings) successfully merged out of 21 pairings) input.## 2275 paired-reads (in 6 unique pairings) successfully merged out of 4704 (in 41 pairings) input.## 101 paired-reads (in 1 unique pairings) successfully merged out of 5639 (in 13 pairings) input.## 1298 paired-reads (in 6 unique pairings) successfully merged out of 8650 (in 46 pairings) input.## 1656 paired-reads (in 6 unique pairings) successfully merged out of 6105 (in 38 pairings) input.## 2470 paired-reads (in 5 unique pairings) successfully merged out of 5246 (in 50 pairings) input.## 12626 paired-reads (in 7 unique pairings) successfully merged out of 16195 (in 44 pairings) input.## 12197 paired-reads (in 9 unique pairings) successfully merged out of 15612 (in 51 pairings) input.## 2782 paired-reads (in 5 unique pairings) successfully merged out of 11521 (in 59 pairings) input.## 316 paired-reads (in 4 unique pairings) successfully merged out of 8333 (in 24 pairings) input.## 6712 paired-reads (in 13 unique pairings) successfully merged out of 14204 (in 91 pairings) input.## 15295 paired-reads (in 14 unique pairings) successfully merged out of 19253 (in 78 pairings) input.## 1776 paired-reads (in 8 unique pairings) successfully merged out of 5459 (in 50 pairings) input.## 1887 paired-reads (in 14 unique pairings) successfully merged out of 12243 (in 152 pairings) input.## 3494 paired-reads (in 6 unique pairings) successfully merged out of 11101 (in 45 pairings) input.## 2260 paired-reads (in 12 unique pairings) successfully merged out of 7762 (in 46 pairings) input.## 7 paired-reads (in 1 unique pairings) successfully merged out of 1959 (in 10 pairings) input.## 318 paired-reads (in 4 unique pairings) successfully merged out of 3762 (in 43 pairings) input.## 1942 paired-reads (in 6 unique pairings) successfully merged out of 6514 (in 24 pairings) input.## 733 paired-reads (in 6 unique pairings) successfully merged out of 9758 (in 67 pairings) input.## 3122 paired-reads (in 8 unique pairings) successfully merged out of 18375 (in 87 pairings) input.## 99 paired-reads (in 2 unique pairings) successfully merged out of 4351 (in 34 pairings) input.## 126 paired-reads (in 4 unique pairings) successfully merged out of 17305 (in 70 pairings) input.## 3975 paired-reads (in 5 unique pairings) successfully merged out of 12309 (in 44 pairings) input.## 56 paired-reads (in 3 unique pairings) successfully merged out of 9555 (in 50 pairings) input.## 1602 paired-reads (in 5 unique pairings) successfully merged out of 9846 (in 68 pairings) input.## 1100 paired-reads (in 7 unique pairings) successfully merged out of 11711 (in 73 pairings) input.## 4210 paired-reads (in 11 unique pairings) successfully merged out of 8690 (in 70 pairings) input.## 1538 paired-reads (in 10 unique pairings) successfully merged out of 7602 (in 42 pairings) input.## 340 paired-reads (in 5 unique pairings) successfully merged out of 7657 (in 57 pairings) input.## 380 paired-reads (in 2 unique pairings) successfully merged out of 8916 (in 71 pairings) input.## 257 paired-reads (in 5 unique pairings) successfully merged out of 8171 (in 38 pairings) input.## 8746 paired-reads (in 17 unique pairings) successfully merged out of 25798 (in 168 pairings) input.## 2235 paired-reads (in 7 unique pairings) successfully merged out of 8257 (in 37 pairings) input.## 1675 paired-reads (in 11 unique pairings) successfully merged out of 14222 (in 80 pairings) input.## 814 paired-reads (in 9 unique pairings) successfully merged out of 20171 (in 105 pairings) input.## 598 paired-reads (in 6 unique pairings) successfully merged out of 4750 (in 45 pairings) input.## 329 paired-reads (in 8 unique pairings) successfully merged out of 11107 (in 68 pairings) input.## 495 paired-reads (in 7 unique pairings) successfully merged out of 11210 (in 49 pairings) input.## 650 paired-reads (in 5 unique pairings) successfully merged out of 10187 (in 33 pairings) input.## 123 paired-reads (in 2 unique pairings) successfully merged out of 2751 (in 36 pairings) input.## 58 paired-reads (in 1 unique pairings) successfully merged out of 4468 (in 50 pairings) input.## 4644 paired-reads (in 9 unique pairings) successfully merged out of 9436 (in 38 pairings) input.## 771 paired-reads (in 6 unique pairings) successfully merged out of 5981 (in 59 pairings) input.## 6498 paired-reads (in 16 unique pairings) successfully merged out of 22488 (in 149 pairings) input.## 3898 paired-reads (in 7 unique pairings) successfully merged out of 7612 (in 50 pairings) input.## 410 paired-reads (in 5 unique pairings) successfully merged out of 19035 (in 96 pairings) input.## 91 paired-reads (in 1 unique pairings) successfully merged out of 11204 (in 86 pairings) input.## 998 paired-reads (in 6 unique pairings) successfully merged out of 11969 (in 90 pairings) input.## No paired-reads (in ZERO unique pairings) successfully merged out of 7 pairings) input.## 0 paired-reads (in 0 unique pairings) successfully merged out of 1 (in 1 pairings) input.## 0 paired-reads (in 0 unique pairings) successfully merged out of 5 (in 1 pairings) input.## No paired-reads (in ZERO unique pairings) successfully merged out of 5 pairings) input.## 0 paired-reads (in 0 unique pairings) successfully merged out of 39 (in 2 pairings) input.## 107 paired-reads (in 5 unique pairings) successfully merged out of 247 (in 12 pairings) input.## 28 paired-reads (in 1 unique pairings) successfully merged out of 28 (in 1 pairings) input.## No paired-reads (in ZERO unique pairings) successfully merged out of 33 pairings) input.## 0 paired-reads (in 0 unique pairings) successfully merged out of 2 (in 1 pairings) input.
## 0 paired-reads (in 0 unique pairings) successfully merged out of 2 (in 1 pairings) input.## 597 paired-reads (in 7 unique pairings) successfully merged out of 12064 (in 136 pairings) input.## 617 paired-reads (in 8 unique pairings) successfully merged out of 12739 (in 116 pairings) input.## 459 paired-reads (in 6 unique pairings) successfully merged out of 6621 (in 81 pairings) input.#this paper used min overlap of 10bp with "nrITS2": https://www.sciencedirect.com/science/article/pii/S0048969721055455#s0010
#I could play with minOverlap parameter to see the effects on merging
# length=30L; overlap=25; mismat=0
# mergers.test <- mergePairs(head(dadaFs, n=length), head(derepFs, n=length), head(dadaRs, n=length), head(derepRs, n=length), verbose=TRUE, minOverlap = overlap, maxMismatch = mismat)
# rm(length,overlap,mismat,mergers.test)The mergePairs(…) function returns a data.frame corresponding to each successfully merged unique sequence. The “forward” and “reverse” columns record which forward and reverse sequence contributed to that merged sequence.
Construct ASV table
We can now construct an amplicon sequence variant table (ASV) table, a higher-resolution version of the OTU table produced by traditional methods.
seqtab <- makeSequenceTable(mergers)
dim(seqtab)## [1] 254 1150# 254 samples
# 1150 ASVs#Post-dada2 quality control
Remove chimeras
A chimera is a single DNA sequence originating when multiple transcripts or DNA sequences get joined. Chimeras can be considered artifacts and be filtered out from the data during processing
The number of unique variants that are chimeras is higher in exact amplicon sequence variant (ASV) methods like DADA2 than they were in OTU methods, as chimeras very close to the real sequences are the most common type of chimera, and those used to be hidden by being lumped into an OTU. So some expectations based on previous OTU processing should be modified a little bit.
Robert Edgar discusses this in more detail in his uchime2 paper: https://doi.org/10.1101/074252
seqtab.nochim <- removeBimeraDenovo(seqtab, method="consensus", multithread=TRUE, verbose=TRUE) #more stringent parameter minFoldParentOverAbundance=2## Identified 509 bimeras out of 1150 input sequences.#Identified 509 bimeras out of 1150 input sequences.
length(sample.names)## [1] 254rownames(seqtab.nochim) <- sample.names
sum(seqtab) # reads## [1] 1440920sum(seqtab.nochim) # reads after removing chimeras## [1] 1374531sum(seqtab.nochim)/sum(seqtab) # proportion of reads remaining## [1] 0.953926100-((sum(seqtab.nochim)/sum(seqtab))*100) # percent of reads removed as chimeras## [1] 4.607404The more important metric here is the fraction of reads removed as bimeras, which is <20% here, so in the range of what we see. It is normal that a much higher fraction of ASVs than reads will be removed as bimeras, because chimeras are highly diverse but usually quite rare. You will see more chimeric ASVs if you sequence deeply, but not a meaningfully higher number of chimeric reads.
If you’re seeing more than 20% of reads being chimeric, you may want to re-examine your PCR protocol in the future. Longer extension times and fewer PCR cycles are both approaches that have been shown to reduce the formation of chimeric amplicons.
Inspect distribution of sequence lengths
Looking distribution of sequence lengths in the non-chimeric ASVs
table(nchar(getSequences(seqtab.nochim)))##
## 171 270 281 298 303 305 306 310 311 312 313 314 315 316 317 318 319 320 321 323
## 1 2 1 1 1 1 1 2 4 4 5 11 4 7 4 4 1 1 1 1
## 324 325 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344
## 2 1 6 2 11 19 17 18 26 13 3 1 38 13 10 1 35 1 17 18
## 345 346 348 349 350 351 352 353 354 355 357 358 359 360 361 363 365 366 367 370
## 28 72 46 32 9 23 3 25 10 1 14 7 1 2 13 8 9 1 11 1
## 371 373 377 387 490
## 2 4 1 2 7sum(table(nchar(getSequences(seqtab.nochim)))) #total ASVs## [1] 641plot(table(nchar(getSequences(seqtab.nochim)))) #peak at 346bp
Unexpected second peak near 490
Remove ASVs with less than 100 reads total
This threshold has been used before for characterizing pollinator microbiomes (Hammer et al. 2020, 2023). Since my pollens are expected to be a lot more simple than a microbiome, I feel this threshold is quite conservative.
seqtab.nochim<-seqtab.nochim[,!!colSums(seqtab.nochim > 100)]Citations for this step: Hammer, T. J., J. C. Dickerson, W. O. McMillan, and N. Fierer. 2020. Heliconius Butterflies Host Characteristic and Phylogenetically Structured Adult-Stage Microbiomes. Applied and Environmental Microbiology 86. Hammer, T. J., J. Kueneman, M. Argueta-Guzmán, Q. S. McFrederick, Lady Grant, W. Wcislo, S. Buchmann, and B. N. Danforth. 2023. Bee breweries: The unusually fermentative, lactobacilli-dominated brood cell microbiomes of cellophane bees. Frontiers in Microbiology 14:1–16.
Remove contaminating sequences with decontam
The steps & info below are largely from this tutorial: https://benjjneb.github.io/decontam/vignettes/decontam_intro.html#necessary-ingredients
The investigation of environmental microbial communities and microbiomes has been transformed by the recent widespread adoption of culture-free high-throughput sequencing methods. In amplicon sequencing a particular genetic locus is amplified from DNA extracted from the community of interest, and then sequenced on a next-generation sequencing platform. In shotgun metagenomics, bulk DNA is extracted from the community of interest and sequenced. Both techniques provide cost-effective and culture-free characterizations of microbial communities.
However, the accuracy of these methods is limited in practice by the introduction of contaminating DNA that was not truly present in the sampled community. This contaminating DNA can come from several sources, such as the reagents used in the sequencing reaction, and can critically interfere with downstream analyses, especially in lower biomass environments. The decontam package provides simple statistical methods to identify and visualize contaminating DNA features, allowing them to be removed and a more accurate picture of sampled communities to be constructed from marker-gene and metagenomics data.
###Prep phyloseq objects
##load packages
library(decontam)
library(readxl)
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## ✔ purrr 1.0.2 ✔ tidyr 1.3.1
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## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors#load sample data
samp.ctrls.conc<-read_excel("/scratch/kls7sg/Bioinformatics/2024-09-27_MiSeq_v3/SampleConc.xlsx")
head(samp.ctrls.conc)## # A tibble: 6 × 5
## SampleID SampleID_AllUnderscores Control Conc_ng.uL Note
## <chr> <chr> <lgl> <dbl> <chr>
## 1 ITS2_2020-6-16_H1 ITS2_2020_6_16_H1 FALSE 60.1 <NA>
## 2 ITS2_2020-6-16_H5 ITS2_2020_6_16_H5 FALSE 53.7 <NA>
## 3 ITS2_2020-6-16_H6 ITS2_2020_6_16_H6 FALSE 41.8 <NA>
## 4 ITS2_2020-6-17_H2 ITS2_2020_6_17_H2 FALSE 45.7 <NA>
## 5 ITS2_2020-6-17_H4 ITS2_2020_6_17_H4 FALSE 75.7 <NA>
## 6 ITS2_2020-6-17_H8 ITS2_2020_6_17_H8 FALSE 59.6 <NA>#filter sample data for just ITS2 samples
samp.ctrls.conc <- samp.ctrls.conc %>% filter(str_starts(SampleID,'ITS2'))
detach("package:tidyverse")#create phyloseq objects with seqtab and sample data (i.e., samp.ctrls.conc)
SAMP <- sample_data(samp.ctrls.conc)
sample_names(SAMP) <- sample_data(SAMP)$SampleID_AllUnderscores
OTU <- otu_table(seqtab.nochim, taxa_are_rows = F, errorIfNULL=TRUE)
sample_names(OTU)<-paste0("ITS2_",sample_names(OTU))
#checking if name formats in SAMP and OTU objects match
head(sample_names(SAMP))## [1] "ITS2_2020_6_16_H1" "ITS2_2020_6_16_H5" "ITS2_2020_6_16_H6"
## [4] "ITS2_2020_6_17_H2" "ITS2_2020_6_17_H4" "ITS2_2020_6_17_H8"head(sample_names(OTU))## [1] "ITS2_2020_6_16_H1" "ITS2_2020_6_16_H5" "ITS2_2020_6_16_H6"
## [4] "ITS2_2020_6_17_H2" "ITS2_2020_6_17_H4" "ITS2_2020_6_17_H8"#checking if number of samples in SAMP and OTU objects match
identical(sample_names(SAMP),sample_names(OTU)) # The safe and reliable way to test two objects for being exactly equal. It returns TRUE in this case, FALSE in every other case.## [1] FALSEmatch(sample_names(SAMP), sample_names(OTU)) # match returns a vector of the positions of (first) matches of its first argument in its second.## [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 NA 14 15 16 17
## [19] 18 19 20 21 22 23 24 25 26 NA 27 28 29 NA 30 31 32 33
## [37] 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
## [55] 52 53 54 55 56 57 58 59 60 61 NA 62 63 64 65 66 67 68
## [73] NA 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85
## [91] 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103
## [109] 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121
## [127] 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139
## [145] 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157
## [163] 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175
## [181] 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 NA 192
## [199] 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210
## [217] 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228
## [235] 229 230 231 232 233 234 235 236 237 238 239 240 NA 241 242 243 244 245
## [253] NA 246 247 248 NA 250 251 252 253 254sample_names(SAMP) %in% sample_names(OTU) # %in% is a more intuitive interface as a binary operator, which returns a logical vector indicating if there is a match or not for its left operand.## [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [13] TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [25] TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE TRUE
## [37] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [49] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [61] TRUE TRUE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [73] FALSE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [85] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [97] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [109] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [121] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [133] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [145] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [157] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [169] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [181] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [193] TRUE TRUE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [205] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [217] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [229] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [241] TRUE TRUE TRUE TRUE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE
## [253] FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE#subset phyloseq object with sample info to contain only the samples present in the OTU obj
SAMP<-prune_samples(sample_names(SAMP) %in% sample_names(OTU), SAMP) #prune_samples() is a method for pruning/filtering unwanted samples by defining those you want to keep. first argument is a logical vector where the kept samples are TRUE, and length is equal to the number of samples in object x; second argument is the phyloseq object to be pruned (subsetted)
#join phyloseq objects into one
physeq = phyloseq(OTU, SAMP)
physeq## phyloseq-class experiment-level object
## otu_table() OTU Table: [ 345 taxa and 253 samples ]
## sample_data() Sample Data: [ 253 samples by 5 sample variables ]slotNames(physeq) #slots for "tax_table", "phy_tree", "refseq" are empty## [1] "otu_table" "tax_table" "sam_data" "phy_tree" "refseq"#reorder physeq
physeq.reord <- physeq
otu_table(physeq.reord) <- otu_table(physeq.reord)[order(sample_data(physeq.reord)$Control),] # reorder so the controls appear lastPlots read numbers for control samples and unknown samples
A quick first look at the library sizes (i.e. the number of reads) in each sample, as a function of whether that sample was a true positive sample or a negative control:
#plot read numbers for control vs sample
df <- as.data.frame(sample_data(physeq)) # Put sample_data into a ggplot-friendly data.frame
df$LibrarySize <- sample_sums(physeq) #sum read numbers
df <- df[order(df$LibrarySize),] #sort by total read numbers
df$Index <- seq(nrow(df)) #create index based on read number sort order
ggplot(data=df, aes(x=Index, y=LibrarySize, color=as.factor(Control))) + geom_point() #plot of read numbers of every library, colored by control vs unk samples
ggplot(data=df, aes(x=Index, y=LibrarySize, color=Conc_ng.uL)) + geom_point() #plot of read numbers of every library, colored by library stock concentration
Identify probable contaminants
The first contaminant identification method we’ll use is the “frequency” method. In this method, the distribution of the frequency of each sequence feature as a function of the input DNA concentration is used to identify contaminants.
The second contaminant identification method is the “prevalence” method. In this method, the prevalence (presence/absence across samples) of each sequence feature in true positive samples is compared to the prevalence in negative controls to identify contaminants.
The final, “combined” method: The frequency and prevalence probabilities are combined with Fisher’s method and used to identify contaminants.
#identify contaminants by frequency & prevalence combined
sample_data(physeq.reord)$is.neg <- sample_data(physeq.reord)$Control == "TRUE"
contamdf.comb <- isContaminant(physeq.reord, method="combined", conc="Conc_ng.uL", neg="is.neg")## Warning in .is_contaminant(seqtab, conc = conc, neg = neg, method = method, :
## Removed 40 samples with zero total counts (or frequency).
## Warning in .is_contaminant(seqtab, conc = conc, neg = neg, method = method, :
## Removed 40 samples with zero total counts (or frequency).table(contamdf.comb$contaminant)##
## FALSE TRUE
## 344 1which(contamdf.comb$contaminant)## [1] 131# Make phyloseq object of presence-absence in negative controls and true samples
ps.pa <- transform_sample_counts(physeq.reord, function(abund) 1*(abund>0))
ps.pa.neg <- prune_samples(sample_data(ps.pa)$Control == "TRUE", ps.pa)
ps.pa.pos <- prune_samples(sample_data(ps.pa)$Control == "FALSE", ps.pa)
# Make data.frame of prevalence in positive and negative samples
df.pa <- data.frame(pa.pos=taxa_sums(ps.pa.pos), pa.neg=taxa_sums(ps.pa.neg),
contaminant=contamdf.comb$contaminant)
# Plot the number of times these taxa were observed in negative controls and positive samples
ggplot(data=df.pa, aes(x=pa.neg, y=pa.pos, color=contaminant)) + geom_point() +
xlab("Prevalence (Negative Controls)") + ylab("Prevalence (True Samples)")
#Samples seem to split pretty cleanly into a branch that shows up mostly in positive samples, and another that shows up mostly in negative controls, and the contaminant assignment (at default probability threshold) has done a good job of identifying those mostly in negative controls.Remove contaminating sequences
#remove contaminants, create seqtab.nochim.nocontam object
physeq.reord.noncontam <- prune_taxa(!contamdf.comb$contaminant, physeq.reord) #create subsetted phyloseq object with the contaminants removed (pruned)
seqtab.nochim.nocontam <- otu_table(physeq.reord.noncontam) #extract otu table from pruned data
class(seqtab.nochim.nocontam) <- "matrix" #coerce to matrix (so we can manipulate and export more easily)## Warning in class(seqtab.nochim.nocontam) <- "matrix": Setting class(x) to
## "matrix" sets attribute to NULL; result will no longer be an S4 objectsubstr(rownames(seqtab.nochim.nocontam), 6, 100) #captures a substring, starting at character 6 (from the left) and continuing up to 100 characters (this will grab sample name without the ITS2 designation)## [1] "2020_6_16_H1"
## [2] "2020_6_16_H5"
## [3] "2020_6_16_H6"
## [4] "2020_6_17_H2"
## [5] "2020_6_17_H4"
## [6] "2020_6_17_H8"
## [7] "2020_6_18_H3"
## [8] "2020_6_18_H7"
## [9] "2020_6_18_H9"
## [10] "2020_6_3_H1"
## [11] "2020_6_3_H5"
## [12] "2020_6_3_H6"
## [13] "2020_6_30_H1"
## [14] "2020_6_30_H6"
## [15] "2020_6_4_H2"
## [16] "2020_6_4_H4"
## [17] "2020_6_4_H8"
## [18] "2020_6_5_H3"
## [19] "2020_6_5_H7"
## [20] "2020_6_5_H9"
## [21] "2020_7_1_H2"
## [22] "2020_7_1_H4"
## [23] "2020_7_1_H8"
## [24] "2020_7_14_H1"
## [25] "2020_7_14_H5"
## [26] "2020_7_14_H6"
## [27] "2020_7_15_H4"
## [28] "2020_7_15_H8"
## [29] "2020_7_16_H3"
## [30] "2020_7_16_H9"
## [31] "2020_7_2_H3"
## [32] "2020_7_2_H7"
## [33] "2020_7_2_H9"
## [34] "2021_6_13_H1"
## [35] "2021_6_13_H3"
## [36] "2021_6_14_H11"
## [37] "2021_6_14_H6"
## [38] "2021_6_14_H7"
## [39] "2021_6_15_H8"
## [40] "2021_6_21_H10"
## [41] "2021_6_21_H12"
## [42] "2021_6_21_H9"
## [43] "2021_6_27_H21"
## [44] "2021_6_27_H22"
## [45] "2021_6_27_H27"
## [46] "2021_6_28_H25"
## [47] "2021_6_28_H26"
## [48] "2021_6_28_H28"
## [49] "2021_6_29_H17"
## [50] "2021_6_29_H23"
## [51] "2021_6_29_H24"
## [52] "2021_6_4_H21"
## [53] "2021_6_4_H22"
## [54] "2021_6_4_H27"
## [55] "2021_6_5_H18"
## [56] "2021_6_5_H25"
## [57] "2021_6_5_H26"
## [58] "2021_6_6_H17"
## [59] "2021_6_6_H24"
## [60] "2021_6_7_H23"
## [61] "2021_7_14_H10"
## [62] "2021_7_20_H27"
## [63] "2021_7_21_H25"
## [64] "2021_7_21_H26"
## [65] "2021_7_21_H28"
## [66] "2021_7_6_H11"
## [67] "2021_7_6_H30"
## [68] "2021_7_6_H6"
## [69] "2021_7_7_H8"
## [70] "2021_7_8_H3"
## [71] "2023_6_12_H3"
## [72] "2023_6_12_H5"
## [73] "2023_6_12_H7"
## [74] "2023_6_13_H6"
## [75] "2023_6_13_H8"
## [76] "2023_6_13_H9"
## [77] "2023_6_14_H3"
## [78] "2023_6_14_H7"
## [79] "2023_6_14_H9"
## [80] "2023_6_16_H5"
## [81] "2023_6_24_H6"
## [82] "2023_6_24_H8"
## [83] "2023_6_25_H2"
## [84] "2023_6_25_H4"
## [85] "2023_6_26_H1"
## [86] "2023_6_26_H7"
## [87] "2023_6_27_H3"
## [88] "2023_6_27_H5"
## [89] "2023_6_8_H1"
## [90] "2023_6_8_H2"
## [91] "2023_6_8_H4"
## [92] "2023_6_9_H2"
## [93] "2023_6_9_H4"
## [94] "2023_7_15_H6"
## [95] "2023_7_16_H4"
## [96] "2023_7_17_H1"
## [97] "2023_7_18_H3"
## [98] "2023_7_18_H7"
## [99] "2023_7_29_H5"
## [100] "2023_7_29_H7"
## [101] "2023_7_30_H8"
## [102] "2023_7_30_H9"
## [103] "2023_7_5_H1"
## [104] "2023_7_5_H2"
## [105] "2023_7_5_H4"
## [106] "2023_7_6_H6"
## [107] "2023_7_6_H8"
## [108] "2023_7_6_H9"
## [109] "2023_7_8_H3"
## [110] "2023_7_8_H5"
## [111] "2023_7_8_H7"
## [112] "2023_8_4_H2"
## [113] "2023_8_4_H5"
## [114] "2023_8_4_H6"
## [115] "2023_8_4_H7"
## [116] "2023_8_4_H8"
## [117] "2023_8_4_H9"
## [118] "Ba001"
## [119] "Ba002"
## [120] "Ba003"
## [121] "Bb001"
## [122] "Bb002"
## [123] "Bb003"
## [124] "Bb004"
## [125] "Bb005"
## [126] "Bb007"
## [127] "Bb008"
## [128] "Bb009"
## [129] "Bb010"
## [130] "Bb011"
## [131] "Bb012"
## [132] "Bb013"
## [133] "Bb014"
## [134] "Bb015"
## [135] "Bb016"
## [136] "Bb017"
## [137] "Bb018"
## [138] "Bb019"
## [139] "Bb020"
## [140] "Bb021"
## [141] "Bb022"
## [142] "Bb023"
## [143] "Bb024"
## [144] "Bb025"
## [145] "Bf001"
## [146] "Bf002"
## [147] "Bf003"
## [148] "Bf004"
## [149] "Bg001"
## [150] "Bg002"
## [151] "Bg003"
## [152] "Bg004"
## [153] "Bg005"
## [154] "Bg006"
## [155] "Bg007"
## [156] "Bg008"
## [157] "Bg009"
## [158] "Bg010"
## [159] "Bg011"
## [160] "Bg012"
## [161] "Bg013"
## [162] "Bg014"
## [163] "Bg015"
## [164] "Bg016"
## [165] "Bg017"
## [166] "Bg018"
## [167] "Bg019"
## [168] "Bi001"
## [169] "Bi002"
## [170] "Bi003"
## [171] "Bi004"
## [172] "Bi005"
## [173] "Bi006"
## [174] "Bi007"
## [175] "CKC0001"
## [176] "ESE0004"
## [177] "KLS0007"
## [178] "KLS0027"
## [179] "KLS0044"
## [180] "KLS0045"
## [181] "KLS0052"
## [182] "KLS0054"
## [183] "KLS0055"
## [184] "KLS0071"
## [185] "KLS0095"
## [186] "KLS0096"
## [187] "KLS0105"
## [188] "KLS0106"
## [189] "KLS0119"
## [190] "KLS0134"
## [191] "KLS0135"
## [192] "KLS0136"
## [193] "KLS0137"
## [194] "KLS0138"
## [195] "KLS0139"
## [196] "KLS0150"
## [197] "KLS0153"
## [198] "KLS0155"
## [199] "KLS0156"
## [200] "KLS0159"
## [201] "KLS0163"
## [202] "KLS0165"
## [203] "KLS0167"
## [204] "KLS0168"
## [205] "KLS0169"
## [206] "KLS0170"
## [207] "KLS0200"
## [208] "KLS0201"
## [209] "KLS0205"
## [210] "KLS0209"
## [211] "KLS0221"
## [212] "KLS0224"
## [213] "KLS0225"
## [214] "KLS0227"
## [215] "KLS0241"
## [216] "KLS0244"
## [217] "KLS0246"
## [218] "KLS0248"
## [219] "KLS0253"
## [220] "KLS0254"
## [221] "KLS0256"
## [222] "KLS0259"
## [223] "KLS0263"
## [224] "KLS0272"
## [225] "SCA0009"
## [226] "SCA0010"
## [227] "SCA0013"
## [228] "ext_neg_ctrl_20230909"
## [229] "ext_neg_ctrl_20230923"
## [230] "ext_neg_ctrl_20230924"
## [231] "ext_neg_ctrl_20231007"
## [232] "ext_neg_ctrl_20231008"
## [233] "ext_neg_ctrl_20231009"
## [234] "ext_neg_ctrl_2024220A"
## [235] "ext_neg_ctrl_2024220B"
## [236] "ext_neg_ctrl_2024221A"
## [237] "ext_neg_ctrl_2024221B"
## [238] "ext_neg_ctrl_2024222A"
## [239] "ext_neg_ctrl_2024222B"
## [240] "ext_neg_ctrl_2024312A"
## [241] "ext_neg_ctrl_2024312B"
## [242] "ext_neg_ctrl_2024314A"
## [243] "ext_neg_ctrl_2024319"
## [244] "ext_neg_ctrl_2024320"
## [245] "pcr_its2_neg_ctrl_20231021_20231119"
## [246] "pcr_its2_neg_ctrl_20231022_20231120"
## [247] "pcr_its2_neg_ctrl_20231023"
## [248] "pcr_its2_neg_ctrl_20240411"
## [249] "pcr_its2_neg_ctrl_20240417"
## [250] "pcr_its2_neg_ctrl_20240418A"
## [251] "pcr_its2_neg_ctrl_20240418B"
## [252] "pcr_its2_neg_ctrl_20240524"
## [253] "pcr_its2_neg_ctrl_Saskia_20240411"identical(substr(rownames(seqtab.nochim.nocontam), 6, 100), rownames(seqtab.nochim)) #they are not in the same order, but this is expected because we had previously reordered nocontam according to total reads## [1] FALSEmatch(substr(rownames(seqtab.nochim.nocontam), 6, 100), rownames(seqtab.nochim)) #returns a vector of the positions of (first) matches of its first argument in its second## [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
## [19] 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
## [37] 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54
## [55] 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72
## [73] 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90
## [91] 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108
## [109] 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126
## [127] 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144
## [145] 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162
## [163] 163 164 165 166 167 168 169 170 171 172 173 174 175 176 194 195 196 197
## [181] 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215
## [199] 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233
## [217] 234 235 236 237 238 239 240 241 252 253 254 177 178 179 180 181 182 183
## [235] 184 185 186 187 188 189 190 191 192 193 242 243 244 245 246 247 248 250
## [253] 251match(rownames(seqtab.nochim),substr(rownames(seqtab.nochim.nocontam), 6, 100)) #returns a vector of the positions of (first) matches of its first argument in its second (switching the order of the arguments reveals that we lost a sample during decontam processing)## [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
## [19] 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
## [37] 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54
## [55] 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72
## [73] 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90
## [91] 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108
## [109] 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126
## [127] 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144
## [145] 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162
## [163] 163 164 165 166 167 168 169 170 171 172 173 174 175 176 228 229 230 231
## [181] 232 233 234 235 236 237 238 239 240 241 242 243 244 177 178 179 180 181
## [199] 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199
## [217] 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217
## [235] 218 219 220 221 222 223 224 245 246 247 248 249 250 251 NA 252 253 225
## [253] 226 227which(is.na(match(rownames(seqtab.nochim),substr(rownames(seqtab.nochim.nocontam), 6, 100)))) #which nochim sample name is NA (ie not found in the nocontam dataset)## [1] 249rownames(seqtab.nochim)[249] #oh yay we lost a negative control!## [1] "pcr_its2_neg_ctrl_20240517"index<-paste0("ITS2_",rownames(seqtab.nochim)[-which(is.na(match(rownames(seqtab.nochim),substr(rownames(seqtab.nochim.nocontam), 6, 100))))]) #save the order of sample names in nochim (and paste ITS2_ in front) as an index for reordering nocontam (BUT not including the row with the negative control that got dropped!)
seqtab.nochim.nocontam <- seqtab.nochim.nocontam[index,,drop=FALSE] #reorder nocontam based on order of sample names in nochim
identical(substr(rownames(seqtab.nochim.nocontam), 6, 100),
rownames(seqtab.nochim)[-which(is.na(match(rownames(seqtab.nochim),
substr(rownames(seqtab.nochim.nocontam), 6, 100))))]) #true! they match exactly## [1] TRUETrack reads through the pipeline
We now inspect the the number of reads that made it through each step in the pipeline to verify everything worked as expected.
# just checking how many samples, reads at various stages
head(out)## reads.in reads.out
## 2020_6_16_H1 8 2
## 2020_6_16_H5 5 3
## 2020_6_16_H6 2 1
## 2020_6_17_H2 14 7
## 2020_6_17_H4 21 8
## 2020_6_17_H8 7 5length(out)/2## [1] 262length(dadaFs)## [1] 254length(dadaRs)## [1] 254length(mergers)## [1] 254length(rowSums(seqtab.nochim))## [1] 254length(rowSums(seqtab.nochim.nocontam)) #oh.. right we lost a sample at the end## [1] 253length(sample.names) ## [1] 254#we'll need to add it back so things match up ughhh
head(rownames(seqtab.nochim.nocontam))## [1] "ITS2_2020_6_16_H1" "ITS2_2020_6_16_H5" "ITS2_2020_6_16_H6"
## [4] "ITS2_2020_6_17_H2" "ITS2_2020_6_17_H4" "ITS2_2020_6_17_H8"head(substr(rownames(seqtab.nochim.nocontam), 6, 100))## [1] "2020_6_16_H1" "2020_6_16_H5" "2020_6_16_H6" "2020_6_17_H2" "2020_6_17_H4"
## [6] "2020_6_17_H8"which(is.na(match(rownames(seqtab.nochim),substr(rownames(seqtab.nochim.nocontam), 6, 100)))) #which nochim sample name is NA (ie not found in the nocontam dataset)## [1] 249rownames(seqtab.nochim)[249]## [1] "pcr_its2_neg_ctrl_20240517"seqtab.nochim.nocontam <- rbind(0, seqtab.nochim.nocontam) ## OVERWRITING AN EXISTING OBJECT (do NOT run this multiple times!!)
rownames(seqtab.nochim.nocontam)[rownames(seqtab.nochim.nocontam) == ""] <- "ITS2_pcr_its2_neg_ctrl_20240517"
index<-paste0("ITS2_",rownames(seqtab.nochim)) #save the order of sample names in nochim (and paste ITS2_ in front) as an index for reordering nocontam
seqtab.nochim.nocontam <- seqtab.nochim.nocontam[index,,drop=FALSE] #reorder nocontam based on order of sample names in nochim
getN <- function(x) sum(getUniques(x))
track <- cbind(out[names(derepFs),], # i only want the samples from "out" which appear in "derepFs" (but in the original tutorial code, you would just call for "out" here)
sapply(dadaFs, getN), # If processing a single sample, replace with getN(dadaFs)
sapply(dadaRs, getN),
sapply(mergers, getN),
rowSums(seqtab.nochim),
rowSums(seqtab.nochim.nocontam)
)
colnames(track) <- c("input", "filtered", "denoisedF", "denoisedR", "merged", "nonchim", "nocontam")
rownames(track) <- sample.names
track## input filtered denoisedF denoisedR merged
## 2020_6_16_H1 8 2 1 1 0
## 2020_6_16_H5 5 3 1 1 0
## 2020_6_16_H6 2 1 1 1 1
## 2020_6_17_H2 14 7 1 2 0
## 2020_6_17_H4 21 8 2 2 0
## 2020_6_17_H8 7 5 2 1 0
## 2020_6_18_H3 54831 28544 28396 28339 12098
## 2020_6_18_H7 22317 14114 14040 13959 6915
## 2020_6_18_H9 28352 9775 9711 9566 6289
## 2020_6_3_H1 29280 17562 17415 17348 11248
## 2020_6_3_H5 33785 17183 16941 16555 5175
## 2020_6_3_H6 21792 9113 8966 8929 4569
## 2020_6_30_H1 20012 11400 11254 11212 7602
## 2020_6_30_H6 3 1 1 1 0
## 2020_6_4_H2 10665 3807 3677 3100 523
## 2020_6_4_H4 16915 7207 7097 7057 4726
## 2020_6_4_H8 38557 20412 20206 19926 11122
## 2020_6_5_H3 22214 13330 13231 13175 9082
## 2020_6_5_H7 23419 13763 13686 13546 8180
## 2020_6_5_H9 6 2 1 1 0
## 2020_7_1_H2 5 1 1 1 0
## 2020_7_1_H4 5 3 2 1 0
## 2020_7_1_H8 95917 59663 59463 59235 43369
## 2020_7_14_H1 128 54 51 12 0
## 2020_7_14_H5 60180 25171 25051 24765 14971
## 2020_7_14_H6 42699 25820 25638 25605 7418
## 2020_7_15_H4 18 4 1 4 0
## 2020_7_15_H8 11 3 1 1 0
## 2020_7_16_H3 7 4 1 2 0
## 2020_7_16_H9 10 2 1 1 0
## 2020_7_2_H3 32569 19284 19066 18980 8781
## 2020_7_2_H7 26559 14455 14327 14295 5466
## 2020_7_2_H9 13587 7696 7629 7531 4279
## 2021_6_13_H1 52222 33662 33575 33236 15660
## 2021_6_13_H3 33682 19584 19421 19277 11578
## 2021_6_14_H11 42866 30473 30410 30271 16707
## 2021_6_14_H6 38199 21451 21374 21027 12751
## 2021_6_14_H7 39022 27667 27597 27472 15278
## 2021_6_15_H8 45176 29183 29090 28930 12859
## 2021_6_21_H10 47845 22468 22375 22276 11442
## 2021_6_21_H12 28369 15386 15032 15104 7963
## 2021_6_21_H9 50720 22706 22622 22434 9979
## 2021_6_27_H21 28962 13598 13523 13417 3102
## 2021_6_27_H22 23010 16586 16506 16061 7729
## 2021_6_27_H27 19777 11031 10976 10866 4747
## 2021_6_28_H25 64701 37109 37021 36969 21916
## 2021_6_28_H26 43084 18011 17891 17837 14493
## 2021_6_28_H28 46901 24520 24334 24379 15568
## 2021_6_29_H17 33867 20380 20194 20230 10311
## 2021_6_29_H23 29020 15119 15055 14912 6896
## 2021_6_29_H24 41165 23804 23677 23572 12637
## 2021_6_4_H21 22236 7846 7674 7627 3278
## 2021_6_4_H22 69217 32343 32201 31571 24879
## 2021_6_4_H27 12414 4382 4335 4267 2757
## 2021_6_5_H18 20882 8700 8586 8522 5251
## 2021_6_5_H25 16223 6167 6082 6027 3509
## 2021_6_5_H26 53993 30751 30612 30424 21365
## 2021_6_6_H17 23116 9885 9736 9366 6862
## 2021_6_6_H24 54777 27479 27276 27229 16440
## 2021_6_7_H23 30858 10700 10602 10557 5426
## 2021_7_14_H10 41103 17609 17557 17509 10586
## 2021_7_20_H27 32048 12038 11956 11900 6471
## 2021_7_21_H25 22936 16172 16109 16035 7762
## 2021_7_21_H26 14 6 4 1 0
## 2021_7_21_H28 4 2 1 1 0
## 2021_7_6_H11 42801 23260 22998 22830 13299
## 2021_7_6_H30 2 1 1 1 0
## 2021_7_6_H6 21771 12438 12280 12261 8306
## 2021_7_7_H8 32290 23534 23491 23427 11417
## 2021_7_8_H3 33448 23041 23016 22964 13604
## 2023_6_12_H3 22492 12263 12057 11929 562
## 2023_6_12_H5 46692 24829 24669 24679 13128
## 2023_6_12_H7 16985 6086 6032 5784 1110
## 2023_6_13_H6 24124 13625 13563 13484 2698
## 2023_6_13_H8 31042 15490 15367 15408 2908
## 2023_6_13_H9 29487 19503 19442 19363 2064
## 2023_6_14_H3 31482 20699 20636 20508 5256
## 2023_6_14_H7 54210 33188 32955 32946 9490
## 2023_6_14_H9 57605 37485 37385 37262 7580
## 2023_6_16_H5 33592 15022 14976 14934 6672
## 2023_6_24_H6 70528 34675 34422 34361 16009
## 2023_6_24_H8 33486 17439 17229 17045 4635
## 2023_6_25_H2 58343 31265 31025 30756 9531
## 2023_6_25_H4 60706 31537 31350 31364 6982
## 2023_6_26_H1 15364 8136 8050 7936 1635
## 2023_6_26_H7 46459 24821 24417 24521 9736
## 2023_6_27_H3 19522 10606 10515 10494 5163
## 2023_6_27_H5 31675 16479 16165 16089 7162
## 2023_6_8_H1 35037 21254 21149 21101 3934
## 2023_6_8_H2 22807 16527 16484 16344 9485
## 2023_6_8_H4 62075 38333 38240 38190 2996
## 2023_6_9_H2 26101 14590 14528 14486 4780
## 2023_6_9_H4 34416 22545 22358 22339 1051
## 2023_7_15_H6 53784 23983 23893 23642 17240
## 2023_7_16_H4 75870 29295 29145 29003 22208
## 2023_7_17_H1 34448 14894 14699 14670 12309
## 2023_7_18_H3 38831 21650 21465 21348 14640
## 2023_7_18_H7 36674 12527 12415 12415 10208
## 2023_7_29_H5 50259 25406 25314 25279 15083
## 2023_7_29_H7 60625 40098 39988 39840 30515
## 2023_7_30_H8 42744 27389 27289 27250 18773
## 2023_7_30_H9 91667 42773 42490 42577 24512
## 2023_7_5_H1 28752 18663 18585 18574 13395
## 2023_7_5_H2 50430 24683 24594 24508 18901
## 2023_7_5_H4 38538 16886 16793 16724 12854
## 2023_7_6_H6 51523 23320 23211 23116 18740
## 2023_7_6_H8 53401 25858 25754 25494 19567
## 2023_7_6_H9 73700 37973 37821 37646 29072
## 2023_7_8_H3 29520 14762 14701 14655 8658
## 2023_7_8_H5 45129 16132 16083 15930 8667
## 2023_7_8_H7 51405 24378 24153 24042 16093
## 2023_8_4_H2 37521 23680 23511 23408 14789
## 2023_8_4_H5 67189 34917 34658 34757 24572
## 2023_8_4_H6 31419 15791 15595 15424 7729
## 2023_8_4_H7 41112 19770 19613 19372 12705
## 2023_8_4_H8 31376 17643 17544 17472 13904
## 2023_8_4_H9 26434 14039 13929 13653 3926
## Ba001 20444 10777 10719 10657 2532
## Ba002 10062 5537 5428 5104 669
## Ba003 20658 9074 8837 8807 1163
## Bb001 11483 6275 6162 6154 2744
## Bb002 13230 7357 7218 7238 3980
## Bb003 21493 11309 11101 11033 2775
## Bb004 19719 10220 10097 10000 1821
## Bb005 10014 5421 5339 5265 2753
## Bb007 1823 1227 1128 1215 805
## Bb008 5432 3419 3400 3376 2603
## Bb009 3344 2193 2149 2159 1600
## Bb010 20264 8989 8843 8569 3461
## Bb011 9862 5075 4946 4719 2232
## Bb012 27072 15928 15826 15646 8121
## Bb013 14186 6123 5958 5297 2009
## Bb014 6342 3127 3046 3001 1185
## Bb015 5798 3045 2944 2884 0
## Bb016 570 318 317 301 105
## Bb017 4100 2279 2226 2189 1291
## Bb018 9265 5380 5267 5074 1745
## Bb019 15898 8859 8655 8596 6343
## Bb020 14554 6218 6130 5936 0
## Bb021 30914 13981 13748 13348 87
## Bb022 43003 24593 24464 24138 11416
## Bb023 50719 24923 24700 24500 7001
## Bb024 54896 36400 36335 36165 1560
## Bb025 27360 16550 16341 16420 6032
## Bf001 50176 22204 22075 21979 5252
## Bf002 32376 18314 18213 18118 535
## Bf003 55364 28486 28314 27968 117
## Bf004 37901 20792 20591 20514 839
## Bg001 35833 19460 19276 19063 5403
## Bg002 25237 14410 14203 13954 4965
## Bg003 53606 31643 31364 30505 5273
## Bg004 46151 21133 20913 20556 3256
## Bg005 33617 18459 18343 18194 2314
## Bg006 67487 30218 30046 29722 9699
## Bg007 41549 14612 14401 14430 7078
## Bg008 19916 12218 12138 11972 3054
## Bg009 38227 21107 21012 20830 10561
## Bg010 57968 35028 34820 34605 1418
## Bg011 45087 25569 25343 25049 3272
## Bg012 53204 32557 32419 32174 11465
## Bg013 30474 11893 11830 11412 153
## Bg014 54710 23693 23482 23446 8480
## Bg015 32118 17641 17481 17363 5360
## Bg016 27580 15525 15399 15311 11926
## Bg017 23952 12481 12358 12245 6243
## Bg018 35296 18766 18585 18070 10936
## Bg019 33265 16055 15926 15835 7820
## Bi001 29569 17384 17243 17069 7192
## Bi002 33740 19912 19718 19661 2960
## Bi003 24732 12910 12828 12773 4813
## Bi004 68416 42207 42002 41962 2019
## Bi005 159 111 102 96 0
## Bi006 60367 38312 38052 37963 3284
## Bi007 48548 30085 29949 29459 18262
## CKC0001 19033 9923 9900 9791 7687
## ESE0004 24596 11887 11769 11544 2705
## ext_neg_ctrl_20230909 45 33 33 20 20
## ext_neg_ctrl_20230923 2 1 1 1 1
## ext_neg_ctrl_20230924 10 5 1 4 0
## ext_neg_ctrl_20231007 6 3 1 1 0
## ext_neg_ctrl_20231008 83 50 48 48 36
## ext_neg_ctrl_20231009 586 358 349 338 272
## ext_neg_ctrl_2024220A 299 131 127 48 44
## ext_neg_ctrl_2024220B 278 129 120 22 0
## ext_neg_ctrl_2024221A 325 159 147 44 0
## ext_neg_ctrl_2024221B 260 130 118 78 9
## ext_neg_ctrl_2024222A 165 88 69 5 0
## ext_neg_ctrl_2024222B 121 76 76 54 54
## ext_neg_ctrl_2024312A 230 104 98 49 49
## ext_neg_ctrl_2024312B 65 28 27 4 0
## ext_neg_ctrl_2024314A 2 1 1 1 1
## ext_neg_ctrl_2024319 37 6 1 2 0
## ext_neg_ctrl_2024320 28 21 18 2 0
## KLS0007 10986 4798 4739 4728 2275
## KLS0027 14230 5767 5734 5649 101
## KLS0044 18225 8955 8835 8735 1298
## KLS0045 12411 6222 6142 6134 1656
## KLS0052 13594 5529 5475 5277 2470
## KLS0054 30236 16389 16364 16201 12626
## KLS0055 29020 15797 15781 15613 12197
## KLS0071 26075 11709 11669 11532 2782
## KLS0095 19181 8701 8671 8336 316
## KLS0096 22779 14500 14407 14250 6712
## KLS0105 31992 19463 19421 19257 15295
## KLS0106 9438 5682 5640 5471 1776
## KLS0119 22458 12665 12445 12409 1887
## KLS0134 23652 11447 11335 11157 3494
## KLS0135 16804 8081 8020 7795 2260
## KLS0136 5426 2509 2245 2158 7
## KLS0137 8678 4076 3967 3811 318
## KLS0138 15102 6754 6704 6537 1942
## KLS0139 18858 10020 9900 9815 733
## KLS0150 28342 18611 18499 18438 3122
## KLS0153 7713 4536 4447 4405 99
## KLS0155 36628 17599 17541 17329 126
## KLS0156 25084 12671 12584 12323 3975
## KLS0159 16354 9988 9902 9589 56
## KLS0163 17520 9958 9873 9903 1602
## KLS0165 19791 12110 12024 11770 1100
## KLS0167 15401 9019 8777 8860 4210
## KLS0168 15333 7722 7663 7622 1538
## KLS0169 16722 8051 7941 7720 340
## KLS0170 19835 9209 9082 8983 380
## KLS0200 19713 8381 8275 8203 257
## KLS0201 48202 26461 26155 26029 8746
## KLS0205 15124 8493 8341 8356 2235
## KLS0209 28115 14812 14550 14401 1675
## KLS0221 33065 20667 20459 20307 814
## KLS0224 12004 5175 5039 4832 598
## KLS0225 23561 11502 11320 11219 329
## KLS0227 26712 11615 11489 11266 495
## KLS0241 21229 10364 10323 10198 650
## KLS0244 6280 2924 2852 2791 123
## KLS0246 9986 4743 4605 4550 58
## KLS0248 23126 9660 9598 9456 4644
## KLS0253 13318 6275 6175 6034 771
## KLS0254 35564 22985 22690 22746 6498
## KLS0256 13505 7938 7808 7683 3898
## KLS0259 41395 19483 19302 19159 410
## KLS0263 23761 11532 11388 11296 91
## KLS0272 20564 12275 12133 12039 998
## pcr_its2_neg_ctrl_20231021_20231119 17 7 1 2 0
## pcr_its2_neg_ctrl_20231022_20231120 4 1 1 1 0
## pcr_its2_neg_ctrl_20231023 28 12 8 5 0
## pcr_its2_neg_ctrl_20240411 11 5 1 1 0
## pcr_its2_neg_ctrl_20240417 564 260 254 39 0
## pcr_its2_neg_ctrl_20240418A 500 309 304 247 107
## pcr_its2_neg_ctrl_20240418B 129 61 42 28 28
## pcr_its2_neg_ctrl_20240517 73 33 32 1 0
## pcr_its2_neg_ctrl_20240524 7 2 2 2 0
## pcr_its2_neg_ctrl_Saskia_20240411 5 2 2 2 0
## SCA0009 26242 12498 12290 12206 597
## SCA0010 30377 13374 13078 12957 617
## SCA0013 14157 6844 6728 6690 459
## nonchim nocontam
## 2020_6_16_H1 0 0
## 2020_6_16_H5 0 0
## 2020_6_16_H6 0 0
## 2020_6_17_H2 0 0
## 2020_6_17_H4 0 0
## 2020_6_17_H8 0 0
## 2020_6_18_H3 11038 11038
## 2020_6_18_H7 6781 6781
## 2020_6_18_H9 5697 5697
## 2020_6_3_H1 10917 10917
## 2020_6_3_H5 4944 4944
## 2020_6_3_H6 4546 4546
## 2020_6_30_H1 7225 7225
## 2020_6_30_H6 0 0
## 2020_6_4_H2 523 523
## 2020_6_4_H4 4289 4289
## 2020_6_4_H8 9863 9863
## 2020_6_5_H3 8877 8877
## 2020_6_5_H7 7764 7764
## 2020_6_5_H9 0 0
## 2020_7_1_H2 0 0
## 2020_7_1_H4 0 0
## 2020_7_1_H8 40336 40336
## 2020_7_14_H1 0 0
## 2020_7_14_H5 14708 14708
## 2020_7_14_H6 6952 6952
## 2020_7_15_H4 0 0
## 2020_7_15_H8 0 0
## 2020_7_16_H3 0 0
## 2020_7_16_H9 0 0
## 2020_7_2_H3 8150 8150
## 2020_7_2_H7 5297 5297
## 2020_7_2_H9 3893 3893
## 2021_6_13_H1 15459 15459
## 2021_6_13_H3 11358 11358
## 2021_6_14_H11 15735 15735
## 2021_6_14_H6 12614 12614
## 2021_6_14_H7 14967 14967
## 2021_6_15_H8 12735 12735
## 2021_6_21_H10 10791 10791
## 2021_6_21_H12 7889 7889
## 2021_6_21_H9 9258 9258
## 2021_6_27_H21 2954 2954
## 2021_6_27_H22 7729 7729
## 2021_6_27_H27 4634 4634
## 2021_6_28_H25 20899 20899
## 2021_6_28_H26 13374 13374
## 2021_6_28_H28 14508 14508
## 2021_6_29_H17 9705 9705
## 2021_6_29_H23 6803 6803
## 2021_6_29_H24 12487 12487
## 2021_6_4_H21 2988 2988
## 2021_6_4_H22 22398 22398
## 2021_6_4_H27 2515 2515
## 2021_6_5_H18 4768 4768
## 2021_6_5_H25 3097 3097
## 2021_6_5_H26 19676 19676
## 2021_6_6_H17 6222 6222
## 2021_6_6_H24 15767 15767
## 2021_6_7_H23 5313 5313
## 2021_7_14_H10 10489 10489
## 2021_7_20_H27 6348 6348
## 2021_7_21_H25 7317 7317
## 2021_7_21_H26 0 0
## 2021_7_21_H28 0 0
## 2021_7_6_H11 12883 12883
## 2021_7_6_H30 0 0
## 2021_7_6_H6 8065 8065
## 2021_7_7_H8 11328 11328
## 2021_7_8_H3 13299 13299
## 2023_6_12_H3 548 548
## 2023_6_12_H5 12464 12464
## 2023_6_12_H7 944 944
## 2023_6_13_H6 2658 2658
## 2023_6_13_H8 2746 2746
## 2023_6_13_H9 1927 1927
## 2023_6_14_H3 5039 5039
## 2023_6_14_H7 9216 9216
## 2023_6_14_H9 7030 7030
## 2023_6_16_H5 6004 6004
## 2023_6_24_H6 14391 14391
## 2023_6_24_H8 4052 4052
## 2023_6_25_H2 8613 8613
## 2023_6_25_H4 6416 6416
## 2023_6_26_H1 1548 1548
## 2023_6_26_H7 9093 9093
## 2023_6_27_H3 4821 4821
## 2023_6_27_H5 6635 6635
## 2023_6_8_H1 3807 3807
## 2023_6_8_H2 9266 9266
## 2023_6_8_H4 2834 2834
## 2023_6_9_H2 4423 4423
## 2023_6_9_H4 968 968
## 2023_7_15_H6 16022 16022
## 2023_7_16_H4 20690 20690
## 2023_7_17_H1 11213 11213
## 2023_7_18_H3 12676 12676
## 2023_7_18_H7 9756 9756
## 2023_7_29_H5 14614 14614
## 2023_7_29_H7 29700 29700
## 2023_7_30_H8 18223 18223
## 2023_7_30_H9 23429 23429
## 2023_7_5_H1 12951 12951
## 2023_7_5_H2 17925 17925
## 2023_7_5_H4 12203 12203
## 2023_7_6_H6 17833 17833
## 2023_7_6_H8 17650 17650
## 2023_7_6_H9 24678 24678
## 2023_7_8_H3 8067 8067
## 2023_7_8_H5 8496 8496
## 2023_7_8_H7 15459 15459
## 2023_8_4_H2 14577 14577
## 2023_8_4_H5 23501 23501
## 2023_8_4_H6 7460 7460
## 2023_8_4_H7 11264 11264
## 2023_8_4_H8 13683 13683
## 2023_8_4_H9 3455 3455
## Ba001 2532 2532
## Ba002 620 620
## Ba003 1122 1122
## Bb001 2592 2592
## Bb002 3761 3761
## Bb003 2234 2234
## Bb004 1395 1395
## Bb005 2564 2564
## Bb007 765 765
## Bb008 1919 1919
## Bb009 1401 1401
## Bb010 3091 3091
## Bb011 2232 2232
## Bb012 6951 6951
## Bb013 1860 1860
## Bb014 1185 1185
## Bb015 0 0
## Bb016 94 94
## Bb017 1291 1291
## Bb018 1745 1745
## Bb019 5732 5732
## Bb020 0 0
## Bb021 87 87
## Bb022 11255 11255
## Bb023 6855 6855
## Bb024 1492 1492
## Bb025 5579 5579
## Bf001 5143 5143
## Bf002 506 506
## Bf003 101 101
## Bf004 738 738
## Bg001 5214 5214
## Bg002 4531 4531
## Bg003 4790 4790
## Bg004 2649 2649
## Bg005 2244 2244
## Bg006 9410 9410
## Bg007 7020 7020
## Bg008 2712 2712
## Bg009 10199 10199
## Bg010 1158 1158
## Bg011 3096 3096
## Bg012 10321 10321
## Bg013 153 153
## Bg014 8201 8201
## Bg015 5135 5135
## Bg016 11634 11634
## Bg017 5715 5715
## Bg018 10706 10706
## Bg019 7529 7529
## Bi001 6727 6727
## Bi002 2773 2773
## Bi003 4689 4689
## Bi004 1910 1910
## Bi005 0 0
## Bi006 2804 2804
## Bi007 16430 16430
## CKC0001 7672 7672
## ESE0004 2446 2446
## ext_neg_ctrl_20230909 0 0
## ext_neg_ctrl_20230923 0 0
## ext_neg_ctrl_20230924 0 0
## ext_neg_ctrl_20231007 0 0
## ext_neg_ctrl_20231008 0 0
## ext_neg_ctrl_20231009 262 262
## ext_neg_ctrl_2024220A 44 44
## ext_neg_ctrl_2024220B 0 0
## ext_neg_ctrl_2024221A 0 0
## ext_neg_ctrl_2024221B 9 9
## ext_neg_ctrl_2024222A 0 0
## ext_neg_ctrl_2024222B 54 54
## ext_neg_ctrl_2024312A 49 49
## ext_neg_ctrl_2024312B 0 0
## ext_neg_ctrl_2024314A 0 0
## ext_neg_ctrl_2024319 0 0
## ext_neg_ctrl_2024320 0 0
## KLS0007 2178 2178
## KLS0027 101 101
## KLS0044 1190 1190
## KLS0045 1605 1605
## KLS0052 2470 2470
## KLS0054 12626 12626
## KLS0055 12092 12092
## KLS0071 2782 1676
## KLS0095 271 271
## KLS0096 6645 6645
## KLS0105 15070 15070
## KLS0106 1685 1685
## KLS0119 1729 1578
## KLS0134 3462 3462
## KLS0135 2090 2090
## KLS0136 7 7
## KLS0137 310 310
## KLS0138 1914 1914
## KLS0139 704 704
## KLS0150 2943 2943
## KLS0153 73 73
## KLS0155 99 99
## KLS0156 3836 3836
## KLS0159 48 48
## KLS0163 1602 1602
## KLS0165 1062 1062
## KLS0167 4207 4207
## KLS0168 1345 1345
## KLS0169 282 282
## KLS0170 380 380
## KLS0200 153 153
## KLS0201 8045 8045
## KLS0205 2091 2091
## KLS0209 1396 1396
## KLS0221 673 673
## KLS0224 577 577
## KLS0225 39 39
## KLS0227 381 381
## KLS0241 608 608
## KLS0244 123 123
## KLS0246 58 58
## KLS0248 4368 4368
## KLS0253 724 724
## KLS0254 6176 6176
## KLS0256 3815 3815
## KLS0259 339 339
## KLS0263 91 91
## KLS0272 917 917
## pcr_its2_neg_ctrl_20231021_20231119 0 0
## pcr_its2_neg_ctrl_20231022_20231120 0 0
## pcr_its2_neg_ctrl_20231023 0 0
## pcr_its2_neg_ctrl_20240411 0 0
## pcr_its2_neg_ctrl_20240417 0 0
## pcr_its2_neg_ctrl_20240418A 69 69
## pcr_its2_neg_ctrl_20240418B 28 28
## pcr_its2_neg_ctrl_20240517 0 0
## pcr_its2_neg_ctrl_20240524 0 0
## pcr_its2_neg_ctrl_Saskia_20240411 0 0
## SCA0009 511 511
## SCA0010 546 546
## SCA0013 405 405head(track)## input filtered denoisedF denoisedR merged nonchim nocontam
## 2020_6_16_H1 8 2 1 1 0 0 0
## 2020_6_16_H5 5 3 1 1 0 0 0
## 2020_6_16_H6 2 1 1 1 1 0 0
## 2020_6_17_H2 14 7 1 2 0 0 0
## 2020_6_17_H4 21 8 2 2 0 0 0
## 2020_6_17_H8 7 5 2 1 0 0 0track<-as.data.frame(track)
library(tidyverse)## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ lubridate::%within%() masks IRanges::%within%()
## ✖ dplyr::collapse() masks Biostrings::collapse(), IRanges::collapse()
## ✖ dplyr::combine() masks Biobase::combine(), BiocGenerics::combine()
## ✖ purrr::compact() masks XVector::compact()
## ✖ purrr::compose() masks ShortRead::compose()
## ✖ dplyr::count() masks matrixStats::count()
## ✖ dplyr::desc() masks IRanges::desc()
## ✖ tidyr::expand() masks S4Vectors::expand()
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::first() masks GenomicAlignments::first(), S4Vectors::first()
## ✖ dplyr::id() masks ShortRead::id()
## ✖ dplyr::lag() masks stats::lag()
## ✖ dplyr::last() masks GenomicAlignments::last()
## ✖ ggplot2::Position() masks BiocGenerics::Position(), base::Position()
## ✖ purrr::reduce() masks GenomicRanges::reduce(), IRanges::reduce()
## ✖ dplyr::rename() masks S4Vectors::rename()
## ✖ lubridate::second() masks GenomicAlignments::second(), S4Vectors::second()
## ✖ lubridate::second<-() masks S4Vectors::second<-()
## ✖ dplyr::slice() masks XVector::slice(), IRanges::slice()
## ✖ tibble::view() masks ShortRead::view()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorshead(track %>% mutate(loss=(input-nocontam)/input)) # calculate % of reads lost from input to final non-chimeric reads## input filtered denoisedF denoisedR merged nonchim nocontam loss
## 2020_6_16_H1 8 2 1 1 0 0 0 1
## 2020_6_16_H5 5 3 1 1 0 0 0 1
## 2020_6_16_H6 2 1 1 1 1 0 0 1
## 2020_6_17_H2 14 7 1 2 0 0 0 1
## 2020_6_17_H4 21 8 2 2 0 0 0 1
## 2020_6_17_H8 7 5 2 1 0 0 0 1head(track %>% filter(str_starts(rownames(.),'ext')|str_starts(rownames(.),'pcr')|str_starts(rownames(.),'rbcL'))) # select just negative control samples## input filtered denoisedF denoisedR merged nonchim
## ext_neg_ctrl_20230909 45 33 33 20 20 0
## ext_neg_ctrl_20230923 2 1 1 1 1 0
## ext_neg_ctrl_20230924 10 5 1 4 0 0
## ext_neg_ctrl_20231007 6 3 1 1 0 0
## ext_neg_ctrl_20231008 83 50 48 48 36 0
## ext_neg_ctrl_20231009 586 358 349 338 272 262
## nocontam
## ext_neg_ctrl_20230909 0
## ext_neg_ctrl_20230923 0
## ext_neg_ctrl_20230924 0
## ext_neg_ctrl_20231007 0
## ext_neg_ctrl_20231008 0
## ext_neg_ctrl_20231009 262# calculate mean and sd for number of reads at each step, separated between negative control and unknown samples
t(track %>%
mutate(loss=(input-nocontam)/input) %>%
group_by(NegCtrl=str_starts(rownames(.),'ext') | str_starts(rownames(.),'pcr') | str_starts(rownames(.),'rbcL')) %>%
summarize(across(input:loss, list(mean=mean, sd=sd), .names="{.col}.{.fn}")) %>% round(.,digits=2)) ## [,1] [,2]
## NegCtrl 0.00 1.00
## input.mean 29100.57 143.70
## input.sd 18757.64 178.38
## filtered.mean 15447.26 74.63
## filtered.sd 10455.56 98.28
## denoisedF.mean 15326.67 69.70
## denoisedF.sd 10418.87 96.29
## denoisedR.mean 15205.79 38.85
## denoisedR.sd 10391.08 77.39
## merged.mean 6344.93 23.00
## merged.sd 6731.37 55.80
## nonchim.mean 5994.25 19.07
## nonchim.sd 6342.17 52.51
## nocontam.mean 5988.71 19.07
## nocontam.sd 6345.53 52.51
## loss.mean 0.82 0.94
## loss.sd 0.13 0.13detach("package:tidyverse") #detaching to avoid conflicts... I'll reload it later when I make plots after taxonomic assignmentAssign taxonomy
The DADA2 package provides a native implementation of the naive Bayesian classifier method for taxonomic assignment. The assignTaxonomy function takes as input a set of sequences to ba classified, and a training set of reference sequences with known taxonomy, and outputs taxonomic assignments with at least minBoot bootstrap confidence.
[insert database name & citation]
Load reference databases
# CHANGE ME to location on your machine
PLANiTS.acc <- "/scratch/kls7sg/Bioinformatics/ReferenceDatabases/ITS-PLANiTS_2020.03.29/ITS2.fasta" # (this database has accession numbers in the header)
# >KU904771.1
# TCAACCCATTGCCCCCTT
PLANiTS.sntx <- "/scratch/kls7sg/Bioinformatics/ReferenceDatabases/ITS-PLANiTS_2020.03.29/ITS2.SINTAX_format.fas" #this database has headers with the entire taxonomy of the associated sequence, with each taxonomic level is separated by a semicolon
# >KU904771.1;tax=p:Chlorophyta,c:Ulvophyceae,o:Cladophorales,f:Cladophoraceae,g:Basicladia,s:unknown Basicladia ;
# TCAACCCATTGCCCCCTTGC
PLANiTS.sntx.kls <- "/scratch/kls7sg/Bioinformatics/ReferenceDatabases/ITS-PLANiTS_2020.03.29/ITS2.SINTAX_format-kls2.fas" # this database is similar to PLANiTS.sntx but with headers cleaned up to look identical to the format of the rbcL database I used (RBCL Database: Bell, Karen (2021). rbcL July 2021. figshare. Dataset. <https://doi.org/10.6084/m9.figshare.14936007.v1>)
# >k_Viridiplantae;p_Chlorophyta;c_Ulvophyceae;o_Cladophorales;f_Cladophoraceae;g_Basicladia;s_unknown Basicladia
# TCAACCCATTGCCCCCTTG
UNITE.ref<-"/scratch/kls7sg/Bioinformatics/ReferenceDatabases/ITS-UNITE_2023.07.25/sh_general_release_dynamic_25.07.2023.fasta" #this database
# >Seifertia_sp|KY231246|SH0985654.09FU|reps|k__Fungi;p__Ascomycota;c__Dothideomycetes;o__Pleosporales;f__Melanommataceae;g__Seifertia;s__Seifertia_sp
# CCGTGGGGATTCGTCCCCATTGAGATAGCACCC...Implement assignTaxonomy function
Sys.time(); t1=Sys.time()## [1] "2024-11-13 17:04:13 EST"taxa.its2 <- assignTaxonomy(getSequences(seqtab.nochim.nocontam), PLANiTS.sntx.kls, multithread = TRUE)
Sys.time(); t2=Sys.time()## [1] "2024-11-13 17:06:38 EST"#if your reference file is in the incorrect format for assignTaxonomy, check out this webpage: https://benjjneb.github.io/dada2/training.html
t2-t1 ## Time difference of 2.428037 mins# daaamn, it completed in 1.76 mins (running with 24 cores on Rivanna and multithread=TRUE)
taxa.its2 <- taxa.its2[,-8] #removing an 8th column that only contains NAs (not sure why it got generated...)##View the taxonomic assignment of all ASV sequences
taxa.its2.print <- taxa.its2; rownames(taxa.its2.print) <- NULL # Removing sequence rownames for display only
head(taxa.its2.print)## Kingdom Phylum Class Order Family
## [1,] "k_Viridiplantae" "p_Streptophyta" "c_NA" "o_Lamiales" "f_Plantaginaceae"
## [2,] "k_Viridiplantae" "p_Streptophyta" "c_NA" "o_Solanales" "f_Solanaceae"
## [3,] "k_Viridiplantae" "p_Streptophyta" "c_NA" "o_Fabales" "f_Fabaceae"
## [4,] "k_Viridiplantae" "p_Streptophyta" "c_NA" "o_Fabales" "f_Fabaceae"
## [5,] "k_Viridiplantae" "p_Streptophyta" "c_NA" "o_Fabales" "f_Fabaceae"
## [6,] "k_Viridiplantae" "p_Streptophyta" "c_NA" "o_Lamiales" "f_Plantaginaceae"
## Genus Species
## [1,] "g_Plantago" NA
## [2,] "g_Solanum" "s_Solanum carolinense"
## [3,] "g_Trifolium" "s_Trifolium repens"
## [4,] "g_Trifolium" "s_Trifolium repens"
## [5,] "g_Trifolium" "s_Trifolium repens"
## [6,] "g_Plantago" "s_Plantago lanceolata"Linking taxonomic assignment of ASVs to sample sequence table
its2.seq <- as.data.frame(t(seqtab.nochim.nocontam)) #sample sequence table; transpose columns to rows (so each sequence appears as a row)
its2.taxa <- as.data.frame(taxa.its2) #assigned sequence taxonomy
#do sample sequences appear in the same order as identified sequences?
identical(rownames(its2.seq), rownames(its2.taxa)) # is true, so we proceed## [1] TRUEmatch(rownames(its2.seq),rownames(its2.taxa)) #this function returns the index where the first argument matches the second argument; if the lists are identical, a sequential list of integers up to the total number of records being compared## [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
## [19] 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
## [37] 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54
## [55] 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72
## [73] 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90
## [91] 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108
## [109] 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126
## [127] 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144
## [145] 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162
## [163] 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180
## [181] 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198
## [199] 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216
## [217] 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234
## [235] 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252
## [253] 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270
## [271] 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288
## [289] 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306
## [307] 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324
## [325] 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342
## [343] 343 344# bind sample sequence table with assigned sequence taxonomy
ITS2.IDs <- cbind(its2.seq,its2.taxa)
# rownames(ITS2.IDs) <- NULL #remove ASV row names (skipping this for now)
#rename samples (remove "ITS2_")
names(ITS2.IDs)## [1] "ITS2_2020_6_16_H1"
## [2] "ITS2_2020_6_16_H5"
## [3] "ITS2_2020_6_16_H6"
## [4] "ITS2_2020_6_17_H2"
## [5] "ITS2_2020_6_17_H4"
## [6] "ITS2_2020_6_17_H8"
## [7] "ITS2_2020_6_18_H3"
## [8] "ITS2_2020_6_18_H7"
## [9] "ITS2_2020_6_18_H9"
## [10] "ITS2_2020_6_3_H1"
## [11] "ITS2_2020_6_3_H5"
## [12] "ITS2_2020_6_3_H6"
## [13] "ITS2_2020_6_30_H1"
## [14] "ITS2_2020_6_30_H6"
## [15] "ITS2_2020_6_4_H2"
## [16] "ITS2_2020_6_4_H4"
## [17] "ITS2_2020_6_4_H8"
## [18] "ITS2_2020_6_5_H3"
## [19] "ITS2_2020_6_5_H7"
## [20] "ITS2_2020_6_5_H9"
## [21] "ITS2_2020_7_1_H2"
## [22] "ITS2_2020_7_1_H4"
## [23] "ITS2_2020_7_1_H8"
## [24] "ITS2_2020_7_14_H1"
## [25] "ITS2_2020_7_14_H5"
## [26] "ITS2_2020_7_14_H6"
## [27] "ITS2_2020_7_15_H4"
## [28] "ITS2_2020_7_15_H8"
## [29] "ITS2_2020_7_16_H3"
## [30] "ITS2_2020_7_16_H9"
## [31] "ITS2_2020_7_2_H3"
## [32] "ITS2_2020_7_2_H7"
## [33] "ITS2_2020_7_2_H9"
## [34] "ITS2_2021_6_13_H1"
## [35] "ITS2_2021_6_13_H3"
## [36] "ITS2_2021_6_14_H11"
## [37] "ITS2_2021_6_14_H6"
## [38] "ITS2_2021_6_14_H7"
## [39] "ITS2_2021_6_15_H8"
## [40] "ITS2_2021_6_21_H10"
## [41] "ITS2_2021_6_21_H12"
## [42] "ITS2_2021_6_21_H9"
## [43] "ITS2_2021_6_27_H21"
## [44] "ITS2_2021_6_27_H22"
## [45] "ITS2_2021_6_27_H27"
## [46] "ITS2_2021_6_28_H25"
## [47] "ITS2_2021_6_28_H26"
## [48] "ITS2_2021_6_28_H28"
## [49] "ITS2_2021_6_29_H17"
## [50] "ITS2_2021_6_29_H23"
## [51] "ITS2_2021_6_29_H24"
## [52] "ITS2_2021_6_4_H21"
## [53] "ITS2_2021_6_4_H22"
## [54] "ITS2_2021_6_4_H27"
## [55] "ITS2_2021_6_5_H18"
## [56] "ITS2_2021_6_5_H25"
## [57] "ITS2_2021_6_5_H26"
## [58] "ITS2_2021_6_6_H17"
## [59] "ITS2_2021_6_6_H24"
## [60] "ITS2_2021_6_7_H23"
## [61] "ITS2_2021_7_14_H10"
## [62] "ITS2_2021_7_20_H27"
## [63] "ITS2_2021_7_21_H25"
## [64] "ITS2_2021_7_21_H26"
## [65] "ITS2_2021_7_21_H28"
## [66] "ITS2_2021_7_6_H11"
## [67] "ITS2_2021_7_6_H30"
## [68] "ITS2_2021_7_6_H6"
## [69] "ITS2_2021_7_7_H8"
## [70] "ITS2_2021_7_8_H3"
## [71] "ITS2_2023_6_12_H3"
## [72] "ITS2_2023_6_12_H5"
## [73] "ITS2_2023_6_12_H7"
## [74] "ITS2_2023_6_13_H6"
## [75] "ITS2_2023_6_13_H8"
## [76] "ITS2_2023_6_13_H9"
## [77] "ITS2_2023_6_14_H3"
## [78] "ITS2_2023_6_14_H7"
## [79] "ITS2_2023_6_14_H9"
## [80] "ITS2_2023_6_16_H5"
## [81] "ITS2_2023_6_24_H6"
## [82] "ITS2_2023_6_24_H8"
## [83] "ITS2_2023_6_25_H2"
## [84] "ITS2_2023_6_25_H4"
## [85] "ITS2_2023_6_26_H1"
## [86] "ITS2_2023_6_26_H7"
## [87] "ITS2_2023_6_27_H3"
## [88] "ITS2_2023_6_27_H5"
## [89] "ITS2_2023_6_8_H1"
## [90] "ITS2_2023_6_8_H2"
## [91] "ITS2_2023_6_8_H4"
## [92] "ITS2_2023_6_9_H2"
## [93] "ITS2_2023_6_9_H4"
## [94] "ITS2_2023_7_15_H6"
## [95] "ITS2_2023_7_16_H4"
## [96] "ITS2_2023_7_17_H1"
## [97] "ITS2_2023_7_18_H3"
## [98] "ITS2_2023_7_18_H7"
## [99] "ITS2_2023_7_29_H5"
## [100] "ITS2_2023_7_29_H7"
## [101] "ITS2_2023_7_30_H8"
## [102] "ITS2_2023_7_30_H9"
## [103] "ITS2_2023_7_5_H1"
## [104] "ITS2_2023_7_5_H2"
## [105] "ITS2_2023_7_5_H4"
## [106] "ITS2_2023_7_6_H6"
## [107] "ITS2_2023_7_6_H8"
## [108] "ITS2_2023_7_6_H9"
## [109] "ITS2_2023_7_8_H3"
## [110] "ITS2_2023_7_8_H5"
## [111] "ITS2_2023_7_8_H7"
## [112] "ITS2_2023_8_4_H2"
## [113] "ITS2_2023_8_4_H5"
## [114] "ITS2_2023_8_4_H6"
## [115] "ITS2_2023_8_4_H7"
## [116] "ITS2_2023_8_4_H8"
## [117] "ITS2_2023_8_4_H9"
## [118] "ITS2_Ba001"
## [119] "ITS2_Ba002"
## [120] "ITS2_Ba003"
## [121] "ITS2_Bb001"
## [122] "ITS2_Bb002"
## [123] "ITS2_Bb003"
## [124] "ITS2_Bb004"
## [125] "ITS2_Bb005"
## [126] "ITS2_Bb007"
## [127] "ITS2_Bb008"
## [128] "ITS2_Bb009"
## [129] "ITS2_Bb010"
## [130] "ITS2_Bb011"
## [131] "ITS2_Bb012"
## [132] "ITS2_Bb013"
## [133] "ITS2_Bb014"
## [134] "ITS2_Bb015"
## [135] "ITS2_Bb016"
## [136] "ITS2_Bb017"
## [137] "ITS2_Bb018"
## [138] "ITS2_Bb019"
## [139] "ITS2_Bb020"
## [140] "ITS2_Bb021"
## [141] "ITS2_Bb022"
## [142] "ITS2_Bb023"
## [143] "ITS2_Bb024"
## [144] "ITS2_Bb025"
## [145] "ITS2_Bf001"
## [146] "ITS2_Bf002"
## [147] "ITS2_Bf003"
## [148] "ITS2_Bf004"
## [149] "ITS2_Bg001"
## [150] "ITS2_Bg002"
## [151] "ITS2_Bg003"
## [152] "ITS2_Bg004"
## [153] "ITS2_Bg005"
## [154] "ITS2_Bg006"
## [155] "ITS2_Bg007"
## [156] "ITS2_Bg008"
## [157] "ITS2_Bg009"
## [158] "ITS2_Bg010"
## [159] "ITS2_Bg011"
## [160] "ITS2_Bg012"
## [161] "ITS2_Bg013"
## [162] "ITS2_Bg014"
## [163] "ITS2_Bg015"
## [164] "ITS2_Bg016"
## [165] "ITS2_Bg017"
## [166] "ITS2_Bg018"
## [167] "ITS2_Bg019"
## [168] "ITS2_Bi001"
## [169] "ITS2_Bi002"
## [170] "ITS2_Bi003"
## [171] "ITS2_Bi004"
## [172] "ITS2_Bi005"
## [173] "ITS2_Bi006"
## [174] "ITS2_Bi007"
## [175] "ITS2_CKC0001"
## [176] "ITS2_ESE0004"
## [177] "ITS2_ext_neg_ctrl_20230909"
## [178] "ITS2_ext_neg_ctrl_20230923"
## [179] "ITS2_ext_neg_ctrl_20230924"
## [180] "ITS2_ext_neg_ctrl_20231007"
## [181] "ITS2_ext_neg_ctrl_20231008"
## [182] "ITS2_ext_neg_ctrl_20231009"
## [183] "ITS2_ext_neg_ctrl_2024220A"
## [184] "ITS2_ext_neg_ctrl_2024220B"
## [185] "ITS2_ext_neg_ctrl_2024221A"
## [186] "ITS2_ext_neg_ctrl_2024221B"
## [187] "ITS2_ext_neg_ctrl_2024222A"
## [188] "ITS2_ext_neg_ctrl_2024222B"
## [189] "ITS2_ext_neg_ctrl_2024312A"
## [190] "ITS2_ext_neg_ctrl_2024312B"
## [191] "ITS2_ext_neg_ctrl_2024314A"
## [192] "ITS2_ext_neg_ctrl_2024319"
## [193] "ITS2_ext_neg_ctrl_2024320"
## [194] "ITS2_KLS0007"
## [195] "ITS2_KLS0027"
## [196] "ITS2_KLS0044"
## [197] "ITS2_KLS0045"
## [198] "ITS2_KLS0052"
## [199] "ITS2_KLS0054"
## [200] "ITS2_KLS0055"
## [201] "ITS2_KLS0071"
## [202] "ITS2_KLS0095"
## [203] "ITS2_KLS0096"
## [204] "ITS2_KLS0105"
## [205] "ITS2_KLS0106"
## [206] "ITS2_KLS0119"
## [207] "ITS2_KLS0134"
## [208] "ITS2_KLS0135"
## [209] "ITS2_KLS0136"
## [210] "ITS2_KLS0137"
## [211] "ITS2_KLS0138"
## [212] "ITS2_KLS0139"
## [213] "ITS2_KLS0150"
## [214] "ITS2_KLS0153"
## [215] "ITS2_KLS0155"
## [216] "ITS2_KLS0156"
## [217] "ITS2_KLS0159"
## [218] "ITS2_KLS0163"
## [219] "ITS2_KLS0165"
## [220] "ITS2_KLS0167"
## [221] "ITS2_KLS0168"
## [222] "ITS2_KLS0169"
## [223] "ITS2_KLS0170"
## [224] "ITS2_KLS0200"
## [225] "ITS2_KLS0201"
## [226] "ITS2_KLS0205"
## [227] "ITS2_KLS0209"
## [228] "ITS2_KLS0221"
## [229] "ITS2_KLS0224"
## [230] "ITS2_KLS0225"
## [231] "ITS2_KLS0227"
## [232] "ITS2_KLS0241"
## [233] "ITS2_KLS0244"
## [234] "ITS2_KLS0246"
## [235] "ITS2_KLS0248"
## [236] "ITS2_KLS0253"
## [237] "ITS2_KLS0254"
## [238] "ITS2_KLS0256"
## [239] "ITS2_KLS0259"
## [240] "ITS2_KLS0263"
## [241] "ITS2_KLS0272"
## [242] "ITS2_pcr_its2_neg_ctrl_20231021_20231119"
## [243] "ITS2_pcr_its2_neg_ctrl_20231022_20231120"
## [244] "ITS2_pcr_its2_neg_ctrl_20231023"
## [245] "ITS2_pcr_its2_neg_ctrl_20240411"
## [246] "ITS2_pcr_its2_neg_ctrl_20240417"
## [247] "ITS2_pcr_its2_neg_ctrl_20240418A"
## [248] "ITS2_pcr_its2_neg_ctrl_20240418B"
## [249] "ITS2_pcr_its2_neg_ctrl_20240517"
## [250] "ITS2_pcr_its2_neg_ctrl_20240524"
## [251] "ITS2_pcr_its2_neg_ctrl_Saskia_20240411"
## [252] "ITS2_SCA0009"
## [253] "ITS2_SCA0010"
## [254] "ITS2_SCA0013"
## [255] "Kingdom"
## [256] "Phylum"
## [257] "Class"
## [258] "Order"
## [259] "Family"
## [260] "Genus"
## [261] "Species"names(ITS2.IDs) <- sub("^ITS2_", "", names(ITS2.IDs)) #remove the "ITS2_" at beginning of column names
names(ITS2.IDs)## [1] "2020_6_16_H1"
## [2] "2020_6_16_H5"
## [3] "2020_6_16_H6"
## [4] "2020_6_17_H2"
## [5] "2020_6_17_H4"
## [6] "2020_6_17_H8"
## [7] "2020_6_18_H3"
## [8] "2020_6_18_H7"
## [9] "2020_6_18_H9"
## [10] "2020_6_3_H1"
## [11] "2020_6_3_H5"
## [12] "2020_6_3_H6"
## [13] "2020_6_30_H1"
## [14] "2020_6_30_H6"
## [15] "2020_6_4_H2"
## [16] "2020_6_4_H4"
## [17] "2020_6_4_H8"
## [18] "2020_6_5_H3"
## [19] "2020_6_5_H7"
## [20] "2020_6_5_H9"
## [21] "2020_7_1_H2"
## [22] "2020_7_1_H4"
## [23] "2020_7_1_H8"
## [24] "2020_7_14_H1"
## [25] "2020_7_14_H5"
## [26] "2020_7_14_H6"
## [27] "2020_7_15_H4"
## [28] "2020_7_15_H8"
## [29] "2020_7_16_H3"
## [30] "2020_7_16_H9"
## [31] "2020_7_2_H3"
## [32] "2020_7_2_H7"
## [33] "2020_7_2_H9"
## [34] "2021_6_13_H1"
## [35] "2021_6_13_H3"
## [36] "2021_6_14_H11"
## [37] "2021_6_14_H6"
## [38] "2021_6_14_H7"
## [39] "2021_6_15_H8"
## [40] "2021_6_21_H10"
## [41] "2021_6_21_H12"
## [42] "2021_6_21_H9"
## [43] "2021_6_27_H21"
## [44] "2021_6_27_H22"
## [45] "2021_6_27_H27"
## [46] "2021_6_28_H25"
## [47] "2021_6_28_H26"
## [48] "2021_6_28_H28"
## [49] "2021_6_29_H17"
## [50] "2021_6_29_H23"
## [51] "2021_6_29_H24"
## [52] "2021_6_4_H21"
## [53] "2021_6_4_H22"
## [54] "2021_6_4_H27"
## [55] "2021_6_5_H18"
## [56] "2021_6_5_H25"
## [57] "2021_6_5_H26"
## [58] "2021_6_6_H17"
## [59] "2021_6_6_H24"
## [60] "2021_6_7_H23"
## [61] "2021_7_14_H10"
## [62] "2021_7_20_H27"
## [63] "2021_7_21_H25"
## [64] "2021_7_21_H26"
## [65] "2021_7_21_H28"
## [66] "2021_7_6_H11"
## [67] "2021_7_6_H30"
## [68] "2021_7_6_H6"
## [69] "2021_7_7_H8"
## [70] "2021_7_8_H3"
## [71] "2023_6_12_H3"
## [72] "2023_6_12_H5"
## [73] "2023_6_12_H7"
## [74] "2023_6_13_H6"
## [75] "2023_6_13_H8"
## [76] "2023_6_13_H9"
## [77] "2023_6_14_H3"
## [78] "2023_6_14_H7"
## [79] "2023_6_14_H9"
## [80] "2023_6_16_H5"
## [81] "2023_6_24_H6"
## [82] "2023_6_24_H8"
## [83] "2023_6_25_H2"
## [84] "2023_6_25_H4"
## [85] "2023_6_26_H1"
## [86] "2023_6_26_H7"
## [87] "2023_6_27_H3"
## [88] "2023_6_27_H5"
## [89] "2023_6_8_H1"
## [90] "2023_6_8_H2"
## [91] "2023_6_8_H4"
## [92] "2023_6_9_H2"
## [93] "2023_6_9_H4"
## [94] "2023_7_15_H6"
## [95] "2023_7_16_H4"
## [96] "2023_7_17_H1"
## [97] "2023_7_18_H3"
## [98] "2023_7_18_H7"
## [99] "2023_7_29_H5"
## [100] "2023_7_29_H7"
## [101] "2023_7_30_H8"
## [102] "2023_7_30_H9"
## [103] "2023_7_5_H1"
## [104] "2023_7_5_H2"
## [105] "2023_7_5_H4"
## [106] "2023_7_6_H6"
## [107] "2023_7_6_H8"
## [108] "2023_7_6_H9"
## [109] "2023_7_8_H3"
## [110] "2023_7_8_H5"
## [111] "2023_7_8_H7"
## [112] "2023_8_4_H2"
## [113] "2023_8_4_H5"
## [114] "2023_8_4_H6"
## [115] "2023_8_4_H7"
## [116] "2023_8_4_H8"
## [117] "2023_8_4_H9"
## [118] "Ba001"
## [119] "Ba002"
## [120] "Ba003"
## [121] "Bb001"
## [122] "Bb002"
## [123] "Bb003"
## [124] "Bb004"
## [125] "Bb005"
## [126] "Bb007"
## [127] "Bb008"
## [128] "Bb009"
## [129] "Bb010"
## [130] "Bb011"
## [131] "Bb012"
## [132] "Bb013"
## [133] "Bb014"
## [134] "Bb015"
## [135] "Bb016"
## [136] "Bb017"
## [137] "Bb018"
## [138] "Bb019"
## [139] "Bb020"
## [140] "Bb021"
## [141] "Bb022"
## [142] "Bb023"
## [143] "Bb024"
## [144] "Bb025"
## [145] "Bf001"
## [146] "Bf002"
## [147] "Bf003"
## [148] "Bf004"
## [149] "Bg001"
## [150] "Bg002"
## [151] "Bg003"
## [152] "Bg004"
## [153] "Bg005"
## [154] "Bg006"
## [155] "Bg007"
## [156] "Bg008"
## [157] "Bg009"
## [158] "Bg010"
## [159] "Bg011"
## [160] "Bg012"
## [161] "Bg013"
## [162] "Bg014"
## [163] "Bg015"
## [164] "Bg016"
## [165] "Bg017"
## [166] "Bg018"
## [167] "Bg019"
## [168] "Bi001"
## [169] "Bi002"
## [170] "Bi003"
## [171] "Bi004"
## [172] "Bi005"
## [173] "Bi006"
## [174] "Bi007"
## [175] "CKC0001"
## [176] "ESE0004"
## [177] "ext_neg_ctrl_20230909"
## [178] "ext_neg_ctrl_20230923"
## [179] "ext_neg_ctrl_20230924"
## [180] "ext_neg_ctrl_20231007"
## [181] "ext_neg_ctrl_20231008"
## [182] "ext_neg_ctrl_20231009"
## [183] "ext_neg_ctrl_2024220A"
## [184] "ext_neg_ctrl_2024220B"
## [185] "ext_neg_ctrl_2024221A"
## [186] "ext_neg_ctrl_2024221B"
## [187] "ext_neg_ctrl_2024222A"
## [188] "ext_neg_ctrl_2024222B"
## [189] "ext_neg_ctrl_2024312A"
## [190] "ext_neg_ctrl_2024312B"
## [191] "ext_neg_ctrl_2024314A"
## [192] "ext_neg_ctrl_2024319"
## [193] "ext_neg_ctrl_2024320"
## [194] "KLS0007"
## [195] "KLS0027"
## [196] "KLS0044"
## [197] "KLS0045"
## [198] "KLS0052"
## [199] "KLS0054"
## [200] "KLS0055"
## [201] "KLS0071"
## [202] "KLS0095"
## [203] "KLS0096"
## [204] "KLS0105"
## [205] "KLS0106"
## [206] "KLS0119"
## [207] "KLS0134"
## [208] "KLS0135"
## [209] "KLS0136"
## [210] "KLS0137"
## [211] "KLS0138"
## [212] "KLS0139"
## [213] "KLS0150"
## [214] "KLS0153"
## [215] "KLS0155"
## [216] "KLS0156"
## [217] "KLS0159"
## [218] "KLS0163"
## [219] "KLS0165"
## [220] "KLS0167"
## [221] "KLS0168"
## [222] "KLS0169"
## [223] "KLS0170"
## [224] "KLS0200"
## [225] "KLS0201"
## [226] "KLS0205"
## [227] "KLS0209"
## [228] "KLS0221"
## [229] "KLS0224"
## [230] "KLS0225"
## [231] "KLS0227"
## [232] "KLS0241"
## [233] "KLS0244"
## [234] "KLS0246"
## [235] "KLS0248"
## [236] "KLS0253"
## [237] "KLS0254"
## [238] "KLS0256"
## [239] "KLS0259"
## [240] "KLS0263"
## [241] "KLS0272"
## [242] "pcr_its2_neg_ctrl_20231021_20231119"
## [243] "pcr_its2_neg_ctrl_20231022_20231120"
## [244] "pcr_its2_neg_ctrl_20231023"
## [245] "pcr_its2_neg_ctrl_20240411"
## [246] "pcr_its2_neg_ctrl_20240417"
## [247] "pcr_its2_neg_ctrl_20240418A"
## [248] "pcr_its2_neg_ctrl_20240418B"
## [249] "pcr_its2_neg_ctrl_20240517"
## [250] "pcr_its2_neg_ctrl_20240524"
## [251] "pcr_its2_neg_ctrl_Saskia_20240411"
## [252] "SCA0009"
## [253] "SCA0010"
## [254] "SCA0013"
## [255] "Kingdom"
## [256] "Phylum"
## [257] "Class"
## [258] "Order"
## [259] "Family"
## [260] "Genus"
## [261] "Species"Plots and summaries of taxonomic assignments
library(tidyverse)## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ lubridate::%within%() masks IRanges::%within%()
## ✖ dplyr::collapse() masks Biostrings::collapse(), IRanges::collapse()
## ✖ dplyr::combine() masks Biobase::combine(), BiocGenerics::combine()
## ✖ purrr::compact() masks XVector::compact()
## ✖ purrr::compose() masks ShortRead::compose()
## ✖ dplyr::count() masks matrixStats::count()
## ✖ dplyr::desc() masks IRanges::desc()
## ✖ tidyr::expand() masks S4Vectors::expand()
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::first() masks GenomicAlignments::first(), S4Vectors::first()
## ✖ dplyr::id() masks ShortRead::id()
## ✖ dplyr::lag() masks stats::lag()
## ✖ dplyr::last() masks GenomicAlignments::last()
## ✖ ggplot2::Position() masks BiocGenerics::Position(), base::Position()
## ✖ purrr::reduce() masks GenomicRanges::reduce(), IRanges::reduce()
## ✖ dplyr::rename() masks S4Vectors::rename()
## ✖ lubridate::second() masks GenomicAlignments::second(), S4Vectors::second()
## ✖ lubridate::second<-() masks S4Vectors::second<-()
## ✖ dplyr::slice() masks XVector::slice(), IRanges::slice()
## ✖ tibble::view() masks ShortRead::view()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorsCreate long data from its2.IDs (sample reads by ASV, with taxa assigned)
Transpose its2.IDs (ASV table by sample) into long format after calculating total reads for each ASV (each row in its2.IDs). After transposing, calculate total reads for each Sample
its2.IDs<-ITS2.IDs %>% mutate(ASVTotalReads = select(., '2020_6_16_H1': 'SCA0013') %>% rowSums()) # total ASV reads
its2.IDs.long<-its2.IDs %>% pivot_longer(cols = c(where(is.numeric), -ASVTotalReads), names_to = "Sample", values_to = "Reads") %>% filter(Reads>0) %>% group_by(Sample) %>% mutate(SampleTotalReads=sum(Reads)) # total Sample reads
#its2.IDs<-partial_join(its2.IDs,___sample-info-data___,"Sample", "SampleName") #join sample info if you want/have itTotal reads? Total Samples? Reads per sample?
1,359,952 reads across all samples 213 samples with 1+ reads 7 to 40,336 reads per sample (mean = 6,391)
sum(its2.IDs$ASVTotalReads) #1361209 reads after removing low-abundance ASVs (1,359,952 reads after removing contaminants)## [1] 1359952its2.IDs %>% select(where(is.numeric), -ASVTotalReads) %>% colnames(.) %>% n_distinct(.) # 254 samples## [1] 254n_distinct(its2.IDs.long$Sample) #213 samples after removing low-abundance ASVs## [1] 213temp<-as.data.frame(its2.IDs %>% select(where(is.numeric), -ASVTotalReads) %>% colSums(.)) # sum up all the reads for all samples that appear in the its2.IDs dataset (basically an ASV table by sample with taxonomic ids)
colnames(temp)<-"TotalReads" #rename column
temp %>% filter(TotalReads==0) # filter to view just samples with 0 reads (these samples get dropped from the data when this dataset is transformed long into its2.IDs.long)## TotalReads
## 2020_6_16_H1 0
## 2020_6_16_H5 0
## 2020_6_16_H6 0
## 2020_6_17_H2 0
## 2020_6_17_H4 0
## 2020_6_17_H8 0
## 2020_6_30_H6 0
## 2020_6_5_H9 0
## 2020_7_1_H2 0
## 2020_7_1_H4 0
## 2020_7_14_H1 0
## 2020_7_15_H4 0
## 2020_7_15_H8 0
## 2020_7_16_H3 0
## 2020_7_16_H9 0
## 2021_7_21_H26 0
## 2021_7_21_H28 0
## 2021_7_6_H30 0
## Bb015 0
## Bb020 0
## Bi005 0
## ext_neg_ctrl_20230909 0
## ext_neg_ctrl_20230923 0
## ext_neg_ctrl_20230924 0
## ext_neg_ctrl_20231007 0
## ext_neg_ctrl_20231008 0
## ext_neg_ctrl_2024220B 0
## ext_neg_ctrl_2024221A 0
## ext_neg_ctrl_2024222A 0
## ext_neg_ctrl_2024312B 0
## ext_neg_ctrl_2024314A 0
## ext_neg_ctrl_2024319 0
## ext_neg_ctrl_2024320 0
## pcr_its2_neg_ctrl_20231021_20231119 0
## pcr_its2_neg_ctrl_20231022_20231120 0
## pcr_its2_neg_ctrl_20231023 0
## pcr_its2_neg_ctrl_20240411 0
## pcr_its2_neg_ctrl_20240417 0
## pcr_its2_neg_ctrl_20240517 0
## pcr_its2_neg_ctrl_20240524 0
## pcr_its2_neg_ctrl_Saskia_20240411 0rm(temp)
hist(its2.IDs.long %>% group_by(Sample) %>% summarise(SumReads=sum(Reads)) %>% select(-Sample) %>% pull(SumReads), xlab="SampleReads", main=NULL) # 
summary(its2.IDs.long %>% group_by(Sample) %>% summarise(SumReads=sum(Reads)) %>% select(-Sample))## SumReads
## Min. : 7
## 1st Qu.: 1401
## Median : 4634
## Mean : 6385
## 3rd Qu.: 9756
## Max. :40336Plots: reads per sample and total reads by sample vs control
# plot of reads per sample for __negative control samples__ (color coded by above/below 2K reads)
its2.IDs.long %>% filter(str_starts(Sample,'ext')|str_starts(Sample,'pcr')|str_starts(Sample,'its2')) %>% group_by(Sample) %>% summarise(SumReads=sum(Reads)) %>%
ggplot(aes(x=Sample,y=SumReads, fill=SumReads<2000))+
geom_col()+
theme(axis.text.x = element_text(angle = 90, vjust = 1, hjust=1))
#plot of reads per sample for __unknown samples__ (color coded by below/above 2K reads)
its2.IDs.long %>% filter(!str_starts(Sample,'ext')&!str_starts(Sample,'pcr')&!str_starts(Sample,'its2')) %>% group_by(Sample) %>% summarise(SumReads=sum(Reads)) %>%
ggplot(aes(x=Sample,y=SumReads, fill=SumReads>2000))+
geom_col()+
theme(axis.text.x = element_text(angle = 90, vjust = 1, hjust=1))
#histogram for __unk samples__
its2.IDs.long %>% filter(!str_starts(Sample,'ext')&!str_starts(Sample,'pcr')&!str_starts(Sample,'its2')) %>% group_by(Sample) %>% summarise(SumReads=sum(Reads)) %>%
ggplot(aes(SumReads))+
geom_histogram(binwidth = 1000, color="black")
#histogram for __neg ctrls__
its2.IDs.long %>% filter(str_starts(Sample,'ext')|str_starts(Sample,'pcr')|str_starts(Sample,'its2')) %>% group_by(Sample) %>% summarise(SumReads=sum(Reads)) %>%
ggplot(aes(SumReads))+
geom_histogram(binwidth = 15, color="black")
How many ASVs total? How many unassigned?
344 total ASVs across all samples 103 of all ASVs were not assigned to species (includes 10 not assigned to genus/family)
length(rownames(its2.IDs)) # 344 total ASVs across all samples## [1] 344its2.IDs%>%filter(is.na(Family)) %>% summarize(n=n()) # 4 of all ASVs were not assigned to family## n
## 1 4its2.IDs%>%filter(is.na(Genus)) %>% summarize(n=n()) # 6 of all ASVs were not assigned to genus (includes 4 not assigned to family)## n
## 1 6its2.IDs%>%filter(is.na(Species)) %>% summarize(n=n()) # 103 of all ASVs were not assigned to species (includes 10 not assigned to genus/family)## n
## 1 109How many reads per ASV?
Most ASVs have very few reads.
# most ASVs have very few total reads
ggplot(its2.IDs, aes(x=ASVTotalReads))+
geom_histogram()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
(most common genera!) How many reads for each ASV species assignment?
I looked at Genera assignments because so many ASVs were not assigned to species.
ggplot(its2.IDs, aes(x=Genus,y=ASVTotalReads))+
geom_col()+
theme(axis.text.x = element_text(angle = 90, vjust = 1, hjust=1))
What percent of reads assigned to spp overall?
Overall, about 80% of reads were assigned to species
its2.IDs %>% filter(is.na(Species)) %>% summarize(sum=sum(ASVTotalReads)) #214,316 reads unassigned to species (out of 1,359,952 reads across all samples total reads)## sum
## 1 407522#after removing low-abund ASVs, there are 285,984 reads unassigned to species (out of 1,898,063 reads total)
(its2.IDs %>% filter(!is.na(Species)) %>% summarize(sum=sum(ASVTotalReads)))/1359952 # ~84% of reads assigned to species; this value may change as the total project reads (denominator) or total assigned reads (numerator) changes with different upstream QC, filtering parameters## sum
## 1 0.7003409What percent of reads assigned to spp for each sample?
some samples with a LOT of unassigned reads how many Unk ASVs per sample
ggplot(its2.IDs.long,aes(x=Sample, y=Reads, fill=!is.na(Species)))+
geom_col(position = "fill")+
labs(x="", y="Proportion of Reads")+
theme(axis.text.x = element_text(angle = 90, vjust = 1, hjust=1))
#some samples with a LOT of unassigned reads
its2.IDs.long %>% filter(is.na(Species)) %>% group_by(Sample) %>% dplyr::summarize(UnkRichness=sum(is.na(Species))) %>%
ggplot(aes(x=Sample, y=UnkRichness))+
geom_col()+
labs(x="",y="Unk ASV Richness")
# how many Unk ASVs per sample
its2.IDs.long %>% group_by(Sample) %>% dplyr::summarize(UnkRichness = sum(is.na(Species)), KnownRichness = sum(!is.na(Species)), UnkProp = UnkRichness/(UnkRichness+KnownRichness))## # A tibble: 213 × 4
## Sample UnkRichness KnownRichness UnkProp
## <chr> <int> <int> <dbl>
## 1 2020_6_18_H3 4 9 0.308
## 2 2020_6_18_H7 1 7 0.125
## 3 2020_6_18_H9 1 4 0.2
## 4 2020_6_30_H1 4 8 0.333
## 5 2020_6_3_H1 8 6 0.571
## 6 2020_6_3_H5 2 3 0.4
## 7 2020_6_3_H6 5 2 0.714
## 8 2020_6_4_H2 0 2 0
## 9 2020_6_4_H4 3 5 0.375
## 10 2020_6_4_H8 4 7 0.364
## # ℹ 203 more rowsits2.IDs.long %>% group_by(Sample) %>% dplyr::summarize(UnkRichness = sum(is.na(Species)), KnownRichness = sum(!is.na(Species)), UnkProp = UnkRichness/(UnkRichness+KnownRichness)) %>%
ggplot(aes(x=Sample, y=UnkProp))+
geom_col()+
labs(x="",y="Proportion of ASVs Unidentified to Species")
How many unassigned ASVs have more than 1000 reads?
#histogram of ASVs unassigned to species (with more than 1000 reads)
its2.IDs %>% filter(is.na(Species)&ASVTotalReads>1000) %>% select(ASVTotalReads)%>%
ggplot(aes(ASVTotalReads))+
geom_histogram(binwidth = 10000, color="black")
#these 39 ASVs represent ~87% of the Species=NA reads (recall: 214,316 reads unassigned to species)
head(its2.IDs %>% filter(is.na(Species)&ASVTotalReads>1000) %>% select(ASVTotalReads)) # common (>1000 reads) ASVs that were not assigned to species (39 ASVs that comprise a total of 187,416 reads)## ASVTotalReads
## TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGACGCCTTCGGGCTGAGGGCACGCCTGCCTGGGCGTCACGCATCGCGTCGTCCCCTCCCATTCCCTCACGGGTTTGGTTATGGGACGGATAATGGCTTCCCGTTAGCTCGGTTAGCCCAAAAAGGATCCCTCATCGACGGATGTCACAACCAGTGGTGGTTGAAAGATCATTGGTGCTGTTGTGCTTCACCCTGTCGCTTGCTAGGGCATCGTCATAAACTAACGGCGTGTAATGCGCCTTCGACCGCGACCCCAGGTCAGACGGGACTACCCGCTGAGTTTAA 172989
## TGCAGAATCCCGTGAACCATCGAGTTTTTGAACGCAAGTTGCGCCCGAAGCCATTCGGCCGAGGGCACGTCTGCCTGGGCGTCACGCATCGCGTCGCCCCAGACCACGCCTCCATATGGGGGATGTGTTTGTCTGGGGCGGAGAATGGTCTCCCGTGCCGTTGGCGCGGTTGGCCTAAAAAGGAGTCCCCTTCGACGGACGCACGGCTAGTGGTGGTTGAAAAAGCCTTCGTATCGAGCCGTGTGTCGTTAGCTGCAAGGGAAGCGCTCTCCATAGACCCTAACGTGTCGTCTCGCGACGATGCTTCGACCGCGACCCCAGGTCAGGCGGGACTACCCGCTGAGTTTAA 22666
## TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGACGCCTTCGGGCTGAGGGCACGCCTGCCTGGGCGTCACGCATCGCGTCGTCCCCTCCCATTCCCTCACGGGTTTGGTTATGGGACGGATAATGGCTTCCCGTTAGCTCGGTTAGCCCAAAAAGGATCCCTCATCGACGGATGTCACAACCAGTGGTGGTTGAAAGATCATTGGTGCTGTTGTGCTTCACCCTGTCGCTTGCTAGGGCATCATCATAAACTAACGGCGTGTAATGCGCCTTCGACCGCGACCCCAGGTCAGACGGGACTACCCGCTGAGTTTAA 20558
## TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGAAGCCATTAGGCCGAGGGCACGCCTGCCTGGGCGTCACACGTCGTTGCACCCCCACTACTCCCTCGGGATTGCGGGGTGCGGATGATGGCCTCCCGTACGCTCCGTCGCGCGGTTGGCATAAATACCAAGTCCTCGGCGACGCACGCCACGACAATCGGTGGTTGCGAAACCTCGGTTGCCCGTCGTGTGCGGTCGTCGCGCATCGGGGGCTCGAAAAAATGCTTGGCTCCGGCTTGGCTTTCAACGCGACCCCAGGTCAGGCGGGGTTACCCGCTGAATTTAA 16425
## TGCAGAATCCCGTGAACCATCGAGTTTTTGAACGCAAGTTGCGCCTGAGACCTTTAGGTTGAGGGCACGTCTGCCTGGGCGTCACACACAGCGTCGCTCCACACCAACCTAGTTGGTAGAGAGCGGATATTGGCCCCCCGAGTCCTTTGGGCACGGTCGGCACAAATATTGGTCCCCGGCAGCGAGTGTCGCGGTCAGCGGTGGTTGTATTTCCTCCAAAGACAAAATGACGCGTTCCTCGTTGCACGTGGATCGAAACGACCCTCGAAAGCCATTTACGGCATTCACCCTGCGACCCCAGGTCAGGCGGGATTACCCGCTGAGTTTAA 12396
## TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGAAGCCATTAGGCCGAGGGCACGCCTGCCTGGGCGTCACACGTCGTTGCCCCCCCCAAACCCCTCGGGAGTTGGGCGGGACGGATGATGGCCTCCCGTGTGCTCTGTCATGCGGTTGGCATAAAAACAAGTCCTCGGCGACTAACGCCACGACAATTGGTGGTTGTCAAACCTCTGTTGCCTATCGTGTGCGCGTGTCGAGCGAGGGCTCAACAAACCATGTTGCATCGATTCGTCGATGCTTTCAACGCGACCCCAGGTCAGGCGGGGTTACCCGCTGAATTTAA 11112length((its2.IDs %>% filter(is.na(Species)&ASVTotalReads>1000) %>% select(ASVTotalReads))$ASVTotalReads)## [1] 43sum(its2.IDs %>% filter(is.na(Species)&ASVTotalReads>1000) %>% select(ASVTotalReads))## [1] 379882What percent of ASV richness by sample is left unassigned?
A mean of 30% of ASVs per sample are unassigned to species, but only a mean of 5% of ASVs per sample are unassigned to Family.
# creating a summary table called "ASVs" to count the number of (un)assigned reads and taxonomic richness for each sample
a<-its2.IDs.long %>% group_by(Sample) %>% summarise(SampleTotalReads=sum(Reads))
b<-its2.IDs.long %>% group_by(Sample) %>% summarise(CountASVs=n())
c<-its2.IDs.long %>% group_by(Sample, .drop=FALSE) %>% filter(is.na(Species)) %>% summarise(ASVs_NoSpp=n())
d<-its2.IDs.long %>% group_by(Sample, .drop=FALSE) %>% filter(is.na(Family)) %>% summarise(ASVs_NoFam=n())
e<-its2.IDs.long %>% group_by(Sample, .drop=FALSE) %>% summarise(Families=n_distinct(Family), Genera=n_distinct(Genus))
ASVs <- cbind(a, b[,2],c[,2],d[,2],e[,-1])
ASVs<- ASVs %>% mutate(PercNoSpp = (ASVs_NoSpp/CountASVs)*100, PercNoFam=(ASVs_NoFam/CountASVs)*100) # number and percent of ASVs not assigned to species or family
summary(ASVs)## Sample SampleTotalReads CountASVs ASVs_NoSpp
## Length:213 Min. : 7 Min. : 1.000 Min. :0.000
## Class :character 1st Qu.: 1401 1st Qu.: 4.000 1st Qu.:1.000
## Mode :character Median : 4634 Median : 7.000 Median :2.000
## Mean : 6385 Mean : 7.643 Mean :2.009
## 3rd Qu.: 9756 3rd Qu.:10.000 3rd Qu.:3.000
## Max. :40336 Max. :22.000 Max. :9.000
## ASVs_NoFam Families Genera PercNoSpp
## Min. :0.00000 Min. :1.000 Min. : 1.000 Min. : 0.000
## 1st Qu.:0.00000 1st Qu.:2.000 1st Qu.: 3.000 1st Qu.: 9.091
## Median :0.00000 Median :3.000 Median : 4.000 Median : 22.222
## Mean :0.02817 Mean :3.559 Mean : 3.892 Mean : 26.448
## 3rd Qu.:0.00000 3rd Qu.:5.000 3rd Qu.: 5.000 3rd Qu.: 36.364
## Max. :2.00000 Max. :9.000 Max. :10.000 Max. :100.000
## PercNoFam
## Min. : 0.0000
## 1st Qu.: 0.0000
## Median : 0.0000
## Mean : 0.3916
## 3rd Qu.: 0.0000
## Max. :28.5714 ggplot(ASVs, aes(x=Sample, y=PercNoSpp))+
geom_col()
ggplot(ASVs, aes(x=Sample, y=PercNoFam))+
geom_col()
How many species per sample?
mean = 3.3 species (range = 1-11 species) per sample
its2.IDs.long %>% filter(!is.na(Species)) %>% group_by(Sample) %>% dplyr::summarize(Richness=n_distinct(Species))## # A tibble: 203 × 2
## Sample Richness
## <chr> <int>
## 1 2020_6_18_H3 3
## 2 2020_6_18_H7 2
## 3 2020_6_18_H9 2
## 4 2020_6_30_H1 4
## 5 2020_6_3_H1 2
## 6 2020_6_3_H5 2
## 7 2020_6_3_H6 2
## 8 2020_6_4_H2 2
## 9 2020_6_4_H4 3
## 10 2020_6_4_H8 4
## # ℹ 193 more rowssummary(its2.IDs.long %>% filter(!is.na(Species)) %>% group_by(Sample) %>% dplyr::summarize(Richness=n_distinct(Species)))## Sample Richness
## Length:203 Min. : 1.000
## Class :character 1st Qu.: 2.000
## Mode :character Median : 3.000
## Mean : 3.217
## 3rd Qu.: 4.000
## Max. :10.000its2.IDs.long %>% filter(!is.na(Species)) %>% group_by(Sample) %>% dplyr::summarize(Richness=n_distinct(Species)) %>%
ggplot(aes(x=Sample, y=Richness))+
geom_col()+
labs(x="",y="Spp Richness")+
theme(axis.text.x = element_text(angle = 90, vjust = 1, hjust=1))
How many reads per species per sample? Proportion of reads?
#numbers of reads per species per sample
ggplot(its2.IDs.long,aes(x=Sample, y=Reads, fill=Species))+
geom_col()+
labs(x="", y="Num of Reads")+
theme(axis.text.x = element_text(angle = 90, vjust = 1, hjust=1), legend.position="none")
#the legend for the above plot
grid::grid.newpage()
grid::grid.draw(cowplot::get_legend(ggplot(its2.IDs.long,aes(x=Sample, y=Reads, fill=Species))+geom_col()))## Warning in get_plot_component(plot, "guide-box"): Multiple components found;
## returning the first one. To return all, use `return_all = TRUE`.
# proportion of reads per species per sample
ggplot(its2.IDs.long,aes(x=Sample, y=Reads, fill=Species))+
geom_bar(position="fill", stat="identity") +
labs(x="", y="Prop of Reads")+
theme(axis.text.x = element_text(angle = 90, vjust = 1, hjust=1), legend.position="none")
Rarefaction with phyloseq
OTU <- otu_table(seqtab.nochim.nocontam, taxa_are_rows = F, errorIfNULL=TRUE)
TAX <- tax_table(taxa.its2)
physeq = phyloseq(OTU, TAX)
physeq## phyloseq-class experiment-level object
## otu_table() OTU Table: [ 344 taxa and 254 samples ]
## tax_table() Taxonomy Table: [ 344 taxa by 7 taxonomic ranks ]slotNames(physeq)## [1] "otu_table" "tax_table" "sam_data" "phy_tree" "refseq"# example of what you can do with phyloseq object, physeq:
# make plots:
# plot_bar(physeq, fill = "Species") # this is basically the same as the plot under 'how many spp per sample?'
class(OTU) <- "matrix" # as.matrix() will do nothing## Warning in class(OTU) <- "matrix": Setting class(x) to "matrix" sets attribute
## to NULL; result will no longer be an S4 objectvegan::rarecurve(OTU, step = 50, xlab = "Sample Size", ylab = "Species", label = TRUE, tidy=T) %>%
ggplot(aes(x=Sample, y=Species, col=Site))+
geom_line()+
labs(x="Read Depth", y="ASVs detected", col="")+
theme(legend.position = "none")+
lims(x=c(0,25000),y=c(0,25))## Warning in vegan::rarecurve(OTU, step = 50, xlab = "Sample Size", ylab =
## "Species", : most observed count data have counts 1, but smallest count is 3## empty rows removed## Warning: Removed 403 rows containing missing values or values outside the scale range
## (`geom_line()`).
Identify taxa missing from its2 reference database
identify families that are not being identified to species
Histogram of read numbers for each ASV
Using threshold of 1000 reads to designate ‘abundant’ vs ‘non-abundant’ ASVs from “How many unassigned ASVs have more than 1000 reads?” ASVs with this many total reads, but which were unassigned to species should be pulled out for futher investigation
its2.IDs.long %>% ggplot(aes(x=Reads)) + geom_histogram()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
its2.IDs.long %>% filter(Reads<1000) %>% ggplot(aes(x=Reads)) + geom_histogram()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Identify abundant unknown ASVs
Here extract the sequences of abundant (more than 1000 reads) but unidentified (Family or Species is NA) ASVs
its2.IDs.long %>% filter(Reads>1000 & is.na(Species)) %>% ggplot(aes(x=Sample, fill=Family))+geom_bar()
#count sequences of abundant (more than 1000 reads) but unidentified ASVs (Species or Family is NA)
dim(its2.IDs %>% filter(ASVTotalReads>1000 & is.na(Family))) # 0 ASVs## [1] 0 262dim(its2.IDs %>% filter(ASVTotalReads>1000 & is.na(Species))) # 39 ASVs## [1] 43 262#extract sequences of abundant unidentified ASVs
head(rownames(its2.IDs %>% filter(ASVTotalReads>1000 & is.na(Species))))## [1] "TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGACGCCTTCGGGCTGAGGGCACGCCTGCCTGGGCGTCACGCATCGCGTCGTCCCCTCCCATTCCCTCACGGGTTTGGTTATGGGACGGATAATGGCTTCCCGTTAGCTCGGTTAGCCCAAAAAGGATCCCTCATCGACGGATGTCACAACCAGTGGTGGTTGAAAGATCATTGGTGCTGTTGTGCTTCACCCTGTCGCTTGCTAGGGCATCGTCATAAACTAACGGCGTGTAATGCGCCTTCGACCGCGACCCCAGGTCAGACGGGACTACCCGCTGAGTTTAA"
## [2] "TGCAGAATCCCGTGAACCATCGAGTTTTTGAACGCAAGTTGCGCCCGAAGCCATTCGGCCGAGGGCACGTCTGCCTGGGCGTCACGCATCGCGTCGCCCCAGACCACGCCTCCATATGGGGGATGTGTTTGTCTGGGGCGGAGAATGGTCTCCCGTGCCGTTGGCGCGGTTGGCCTAAAAAGGAGTCCCCTTCGACGGACGCACGGCTAGTGGTGGTTGAAAAAGCCTTCGTATCGAGCCGTGTGTCGTTAGCTGCAAGGGAAGCGCTCTCCATAGACCCTAACGTGTCGTCTCGCGACGATGCTTCGACCGCGACCCCAGGTCAGGCGGGACTACCCGCTGAGTTTAA"
## [3] "TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGACGCCTTCGGGCTGAGGGCACGCCTGCCTGGGCGTCACGCATCGCGTCGTCCCCTCCCATTCCCTCACGGGTTTGGTTATGGGACGGATAATGGCTTCCCGTTAGCTCGGTTAGCCCAAAAAGGATCCCTCATCGACGGATGTCACAACCAGTGGTGGTTGAAAGATCATTGGTGCTGTTGTGCTTCACCCTGTCGCTTGCTAGGGCATCATCATAAACTAACGGCGTGTAATGCGCCTTCGACCGCGACCCCAGGTCAGACGGGACTACCCGCTGAGTTTAA"
## [4] "TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGAAGCCATTAGGCCGAGGGCACGCCTGCCTGGGCGTCACACGTCGTTGCACCCCCACTACTCCCTCGGGATTGCGGGGTGCGGATGATGGCCTCCCGTACGCTCCGTCGCGCGGTTGGCATAAATACCAAGTCCTCGGCGACGCACGCCACGACAATCGGTGGTTGCGAAACCTCGGTTGCCCGTCGTGTGCGGTCGTCGCGCATCGGGGGCTCGAAAAAATGCTTGGCTCCGGCTTGGCTTTCAACGCGACCCCAGGTCAGGCGGGGTTACCCGCTGAATTTAA"
## [5] "TGCAGAATCCCGTGAACCATCGAGTTTTTGAACGCAAGTTGCGCCTGAGACCTTTAGGTTGAGGGCACGTCTGCCTGGGCGTCACACACAGCGTCGCTCCACACCAACCTAGTTGGTAGAGAGCGGATATTGGCCCCCCGAGTCCTTTGGGCACGGTCGGCACAAATATTGGTCCCCGGCAGCGAGTGTCGCGGTCAGCGGTGGTTGTATTTCCTCCAAAGACAAAATGACGCGTTCCTCGTTGCACGTGGATCGAAACGACCCTCGAAAGCCATTTACGGCATTCACCCTGCGACCCCAGGTCAGGCGGGATTACCCGCTGAGTTTAA"
## [6] "TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGAAGCCATTAGGCCGAGGGCACGCCTGCCTGGGCGTCACACGTCGTTGCCCCCCCCAAACCCCTCGGGAGTTGGGCGGGACGGATGATGGCCTCCCGTGTGCTCTGTCATGCGGTTGGCATAAAAACAAGTCCTCGGCGACTAACGCCACGACAATTGGTGGTTGTCAAACCTCTGTTGCCTATCGTGTGCGCGTGTCGAGCGAGGGCTCAACAAACCATGTTGCATCGATTCGTCGATGCTTTCAACGCGACCCCAGGTCAGGCGGGGTTACCCGCTGAATTTAA"rownames(its2.IDs %>% filter(ASVTotalReads>1000 & is.na(Species)))[1] #the first ASV## [1] "TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGACGCCTTCGGGCTGAGGGCACGCCTGCCTGGGCGTCACGCATCGCGTCGTCCCCTCCCATTCCCTCACGGGTTTGGTTATGGGACGGATAATGGCTTCCCGTTAGCTCGGTTAGCCCAAAAAGGATCCCTCATCGACGGATGTCACAACCAGTGGTGGTTGAAAGATCATTGGTGCTGTTGTGCTTCACCCTGTCGCTTGCTAGGGCATCGTCATAAACTAACGGCGTGTAATGCGCCTTCGACCGCGACCCCAGGTCAGACGGGACTACCCGCTGAGTTTAA"#" "BLAST search for the first ASV came back with 100% identity to several Carduus spp (including Carduus acanthoides!!)
View all ASVs with >1000 reads unassigned to species
knitr::kable(its2.IDs %>%
select(Kingdom:ASVTotalReads) %>%
filter(ASVTotalReads>1000 & is.na(Species)),
row.names = FALSE)| Kingdom | Phylum | Class | Order | Family | Genus | Species | ASVTotalReads |
|---|---|---|---|---|---|---|---|
| k_Viridiplantae | p_Streptophyta | c_NA | o_Lamiales | f_Plantaginaceae | g_Plantago | NA | 172989 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Asterales | f_Asteraceae | g_Carduus | NA | 22666 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Lamiales | f_Plantaginaceae | g_Plantago | NA | 20558 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Rosales | f_Rosaceae | g_Prunus | NA | 16425 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Ranunculales | f_Ranunculaceae | g_Ranunculus | NA | 12396 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Rosales | f_Rosaceae | g_Rubus | NA | 11112 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Asterales | f_Asteraceae | g_Cichorium | NA | 10335 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Lamiales | f_Oleaceae | g_Ligustrum | NA | 9977 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Rosales | f_Rosaceae | g_Prunus | NA | 6619 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Rosales | f_Rosaceae | g_Rubus | NA | 5945 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Rosales | f_Rosaceae | g_Rubus | NA | 5384 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Rosales | f_Rosaceae | g_Prunus | NA | 5369 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Asterales | f_Asteraceae | g_Solidago | NA | 5003 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Malpighiales | f_Violaceae | g_Viola | NA | 4901 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Fabales | f_Fabaceae | g_Trifolium | NA | 4789 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Rosales | f_Rosaceae | g_Rubus | NA | 4605 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Rosales | f_Rosaceae | g_Rubus | NA | 4439 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Rosales | f_Rosaceae | g_Prunus | NA | 4329 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Ericales | f_Polemoniaceae | g_Polemonium | NA | 3792 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Asterales | f_Asteraceae | g_Cichorium | NA | 3561 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Rosales | f_Rosaceae | g_Prunus | NA | 3375 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Ericales | f_Polemoniaceae | g_Polemonium | NA | 3161 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Rosales | f_Rosaceae | g_Photinia | NA | 2783 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Malpighiales | f_Violaceae | g_Viola | NA | 2719 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Ranunculales | f_Ranunculaceae | g_Ranunculus | NA | 2689 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Ericales | f_Ericaceae | g_Vaccinium | NA | 2663 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Fagales | f_Fagaceae | g_Quercus | NA | 2647 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Rosales | f_Rosaceae | g_Prunus | NA | 2451 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Lamiales | f_Scrophulariaceae | g_Verbascum | NA | 2450 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Fagales | f_Fagaceae | g_Quercus | NA | 2449 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Rosales | f_Rosaceae | g_Photinia | NA | 1857 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Asterales | f_Asteraceae | g_Carduus | NA | 1852 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Asterales | f_Asteraceae | g_Solidago | NA | 1500 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Rosales | f_Rosaceae | g_Rosa | NA | 1424 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Rosales | f_Rosaceae | g_Prunus | NA | 1408 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Rosales | f_Rosaceae | g_Photinia | NA | 1317 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Ranunculales | f_Ranunculaceae | g_Ranunculus | NA | 1306 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Lamiales | f_Oleaceae | g_Ligustrum | NA | 1271 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Asterales | f_Asteraceae | g_Centaurea | NA | 1112 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Rosales | f_Rosaceae | g_Photinia | NA | 1098 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Fagales | f_Fagaceae | g_Quercus | NA | 1074 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Rosales | f_Rosaceae | g_Rubus | NA | 1049 |
| k_Viridiplantae | p_Streptophyta | c_NA | o_Ranunculales | f_Ranunculaceae | g_Ranunculus | NA | 1033 |
Export sequence assignments and accessories for all samples (double check path!)
#writepath:"/scratch/kls7sg/Bioinformatics/RMarkdown/ITS2_bioinformatics_files/"
#altwritepath:"/Users/kelseyschoenemann/Desktop/Bioinformatics/RMarkdown/ITS2_bioinformatics_files"
# save table tracking reads through the pipeline
write.csv(track, file="/scratch/kls7sg/Bioinformatics/RMarkdown/ITS2_bioinformatics_files/track.csv")
# save all ASVs with >1000 reads unassigned to species
save<-as.data.frame(rownames(its2.IDs %>% filter(ASVTotalReads>1000 & is.na(Species))))
write.csv(save, file="/scratch/kls7sg/Bioinformatics/RMarkdown/ITS2_bioinformatics_files/UnkSpp_ITS2_ASVs.csv")
# seqtab.nochim.nocontam for phyloseq obj creation
write.csv(seqtab.nochim.nocontam, file="/scratch/kls7sg/Bioinformatics/RMarkdown/ITS2_bioinformatics_files/seqtab.nochim.nocontam.csv")
# taxa.ITS2 for phyloseq obj creation
write.csv(taxa.its2, file="/scratch/kls7sg/Bioinformatics/RMarkdown/ITS2_bioinformatics_files/taxa.ITS2.csv")
# its2.IDs
write.csv(its2.IDs, file="/scratch/kls7sg/Bioinformatics/RMarkdown/ITS2_bioinformatics_files/its2.IDs.csv")
# its2.IDs.long
write.csv(its2.IDs.long, file="/scratch/kls7sg/Bioinformatics/RMarkdown/ITS2_bioinformatics_files/its2.IDs.long.csv")